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PROCEEDINGS

ICAET - 2014 INTERNATIONAL CONFERENCE ON ADVANCEMENTS IN ENGINEERING AND TECHNOLOGY

Sponsored By INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT ((Registered Under Indian Trust Act, 1882)

Technical Program 19TH October, 2014 Hotel NRS Sakithyan, Chennai

Organized By INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT

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Copyright ÂŠ 2014 by IAETSD All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written consent of the publisher.

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Proceedings preparation, editing and printing are sponsored by INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT COMPANY

About IAETSD: The International Association of Engineering and Technology for Skill Development (IAETSD) is a Professional and non-profit conference organizing company devoted to promoting social, economic, and technical advancements around the world by conducting international academic conferences in various Engineering fields around the world. IAETSD organizes multidisciplinary conferences for academics and professionals in the fields of Engineering. In order to strengthen the skill development of the students IAETSD has established. IAETSD is a meeting place where Engineering students can share their views, ideas, can improve their technical knowledge, can develop their skills and for presenting and discussing recent trends in advanced technologies, new educational environments and innovative technology learning ideas. The intention of IAETSD is to expand the knowledge beyond the boundaries by joining the hands with students, researchers, academics and industrialists etc, to explore the technical knowledge all over the world, to publish proceedings. IAETSD offers opportunities to learning professionals for the exploration of problems from many disciplines of various Engineering fields to discover innovative solutions to implement innovative ideas. IAETSD aimed to promote upcoming trends in Engineering.

About ICCIET: The aim objective of ICAET is to present the latest research and results of scientists related to all engineering departmentsâ&#x20AC;&#x2122; topics. This conference provides opportunities for the different areas delegates to exchange new ideas and application experiences face to face, to establish business or research relations and to find global partners for future collaboration. We hope that the conference results constituted significant contribution to the knowledge in these up to date scientific field. The organizing committee of conference is pleased to invite prospective authors to submit their original manuscripts to ICAET 2014. All full paper submissions will be peer reviewed and evaluated based on originality, technical and/or research content/depth, correctness, relevance to conference, contributions, and readability. The conference will be held every year to make it an ideal platform for people to share views and experiences in current trending technologies in the related areas.

Conference Advisory Committee:

Dr. P Paramasivam, NUS, Singapore Dr. Ganapathy Kumar, Nanometrics, USA Mr. Vikram Subramanian, Oracle Public cloud Dr. Michal Wozniak, Wroclaw University of Technology, Dr. Saqib Saeed, Bahria University, Mr. Elamurugan Vaiyapuri, tarkaSys, California Mr. N M Bhaskar, Micron Asia, Singapore Dr. Mohammed Yeasin, University of Memphis Dr. Ahmed Zohaa, Brunel university Kenneth Sundarraj, University of Malaysia Dr. Heba Ahmed Hassan, Dhofar University, Dr. Mohammed Atiquzzaman, University of Oklahoma, Dr. Sattar Aboud, Middle East University, Dr. S Lakshmi, Oman University

Conference Chairs and Review committee:

Dr. Shanti Swaroop, Professor IIT Madras Dr. G Bhuvaneshwari, Professor, IIT, Delhi Dr. Krishna Vasudevan, Professor, IIT Madras Dr.G.V.Uma, Professor, Anna University Dr. S Muttan, Professor, Anna University Dr. R P Kumudini Devi, Professor, Anna University Dr. M Ramalingam, Director (IRS) Dr. N K Ambujam, Director (CWR), Anna University Dr. Bhaskaran, Professor, NIT, Trichy Dr. Pabitra Mohan Khilar, Associate Prof, NIT, Rourkela Dr. V Ramalingam, Professor, Dr.P.Mallikka, Professor, NITTTR, Taramani Dr. E S M Suresh, Professor, NITTTR, Chennai Dr. Gomathi Nayagam, Director CWET, Chennai Prof. S Karthikeyan, VIT, Vellore Dr. H C Nagaraj, Principal, NIMET, Bengaluru Dr. K Sivakumar, Associate Director, CTS. Dr. Tarun Chandroyadulu, Research Associate, NAS

ICAET - 2014 PROCEEDINGS 1

Location-Based Services Using Autonomous GPS

Performance Analysis of Discrete Cosine Transform based image compression

The World’s Smallest Computer For Programmers and App Developers(Raspberry Pi)

Enhancing Vehicle to Vehicle Safety Message Transmission Using Randomized Algorithm

An Efficient and Accurate Misbehavior Detection Scheme in Adversary Environment

A FRAMEWORK FOR SECURE DATA TRANSMISSION IN DEFENSE NETWORK

Load Stabilizing and Energy Conserving Routing Protocol for Wireless Sensor Networks

Multi-View and Multi Band Face Recognition Survey

A SURVEY ON ONE CLASS CLUSTERING HIERARCHY FOR PERFORMING DATA LINKAGE

Dense Dielectric Patch Array Antenna - A New Kind of Low-Profile Antenna Element For 5G Cellular Networks

Advanced mobile signal jammer for GSM, CDMA and 3G Networks with prescheduled time duration using ARM7 TDMI processor based LPC2148 controller

Removal of a Model Textile Dye from Effluent using fenugreek powder as an adsorbent

Artifact Facet Ranking and It’s Application: A Survey

MOBILE ICU USING ANDROID

PURIFICATION OF WATER BY NATURAL ADSORPTION PROCESS

Secure Data Sharing of Multi-Owner Groups in Cloud

IMPLEMENTATION OF A WIRELESS SENSOR NETWORK PLATFORM FOR MONITORING TEMPERATURE IN A FOREST AREA

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Location-Based Services Using Autonomous GPS R. Jegadeeswari

S. Parameswaran

Department of Computer Science and Engineering, M.E. Scholar, Anna University, Sree Sowdambika College of Engineering, Aruppukottai, TamilNadu, India. ragavi.jeri@gmail.com

Department of Computer Science and Engineering, Assistant Professor, Anna University, Sree Sowdambika College of Engineering, Aruppikottai, TamilNadu, India. eswar232000@gmail.com

Abstract—In a mobile era, people need to know about everything at any place and any time. To achieve this need, Location Based Services (LBS) can be the solution for their search. Normally, LBS are achieved with the help of signals of the service provider of that particular mobile. But it is not appropriate if there is poor/no availability of signal strength. Therefore it might be less efficient or even completely useless in some circumstances. Most of the existed LBS consume more battery power, long time to make connection to the server and cost. To overcome this problem, the proposed Android App developed with the Autonomous GPS to track the location of a user with the help of the device’s location services. The incentive of this App is, “To aid with the precise information of current location of a person in real time”. This Android APP is designed to find and tag the services and people where they are located with the concept of Autonomous GPS. These autonomous GPS find the user location from the mobile’s device and it is in-built with smart phones. It works faster with reduced cost compared to the existing system. Keywords— Android operating system, LBS, Autonomous GPS, Google Map.

I. INTRODUCTION 1.1 ANDROID Android is an open source, mobile operating system (OS) based on the Linux kernel, developed by the Open Handset Alliance, led by Google, and other companies. The latest version of Android is 4.4 KitKat. Mobile applications can be build using Android and iOS. An Android app is a software application running on the Android platform. Because the Android platform is built for mobile devices, a typical Android app is designed for a Smartphone or a tablet PC running on the Android OS. Android apps are available in the Google Play Store (formerly known as the Android Market), Amazon AppStore, and 1Mobile market and on various Android App-focused sites.  ANDROID BENEFITS AND LIMITATIONS Benefits of an Android are scheduled as: • Open source • Android scales to all devices • Time for a change • Third party development is encouraged. Android has following limitations: • Not hold by any huge corporation yet except HTC

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• Not support a few applications similar to Firefox • Several restrictions exist in blue tooth 1.2 LBS A Location based services (LBS) is an information and entertainment services, available with mobile devices through the mobile network and utilizing the ability to make use of geographical position of the mobile device. LBS services can be used in a mixture of contexts, such as health, work, personal life, etc. It comprises parcel tracking and vehicle tracking services. LBS have two foremost actions, that is: 1. Finding the location of user 2. Utilizing this information to offer as a service. Location based Services can be classified into 3 categories: A) Public Safety/Emergency Services B) Consumer Services Some cases of location based Services are:  To determine the nearest business or service, such as an Bank or Hotels  Getting alerts, such as notification of Sale in Shopping Mall or news of Traffic Jam nearby  Receiving the location of the stolen phone.  LOCATION-BASED SERVICES – APPLICATIONS In order to provide more useful, attractive and engaging social networks, apps and services location-components have been added to new innovative projects. I have catalogued some of the applications of LBS in the following way:  Marketing  Emergency  Information Services  Navigation  Location Based Social Media  Mobile Location-Based Gaming  Sports  Billing  Geo-tagging  Tracking  Augmented Reality The remainder of this paper is organized as follows. The background and related work of Autonomous GPS

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and other techniques are discussed in Section II. The methodology of LBS components is presented in Section III. Android application: working with use of GPS, Google Maps API is explained in Section IV and the idea of proposed system is evaluated in Section V. Section VI concludes this paper. Future scope of this application is conferred in Section VII. II. BACKGROUND AND RELATED WORK 2.1 Autonomous GPS The Global Positioning System (GPS) is a space- based satellite steering system that includes 24 satellites placed network into orbit by the U.S. Department of Defense. On Earth, GPS receivers take this signal information from many satellites and utilize triangulation to determine the user’s precise location. Cellular networks are being used to “fill in gaps” in transmission signals. Today, there are three different transmission modes being used in community corrections to carry the deliverance of accurate, reliable signals to GPS tracking receivers and overcome geographical or atmospheric challenges. These modes include:  Receiving signals via the GPS satellite network only (Autonomous GPS);  A combination of GPS satellite data with support from a cellular network (Assisted GPS);  A method that measures signals from nearby cellular towers and reports the time/distance readings back to the locating towers (Advanced Forward Link Trilateration) to determine an approximate location of the GPS receiver. In the proposed system, we use autonomous GPS for tracking the user’s location from the mobile device. It offers location and time information in all weather conditions, anywhere on or near the Earth where there is an unobstructed line of sight to four or more GPS satellites. On the ground, any GPS receiver contains a computer that "triangulates" its own position by receiving bearings from at least three satellites. The result is provided in the form of a geographic position longitude and latitude - to, for most receivers, w i t h i n a n a c c u r a c y o f 1 0 t o 1 0 0 meters. Software applications can then use those coordinates to give driving or walking directions.

Figure.2.1: GPS Accuracy and Precision The accuracy expected to be obtained using a GPS receiver will vary according to the overall system used. While accuracy level actually achieved will depend upon many factors, typical estimations of the level of GPS accuracy can be given. GPS system GPS with S/A activated GPS without S/A activated GPS with WAAS Differential GPS

Expected GPS accuracy (meters) ±100 ±15 ±3 ±5

B. Levels of Accuracy The following graph shows the accuracy levels of all currently available systems. The vertical axis is the expected accuracy or error level, shown both in centimeters and meters. The horizontal axis is the distance along the earth's surface between the reference station and the remote user. If there is no reference station, the line is drawn all the way to 10,000 km, all over the earth.

A. GPS Accuracy & Precision One of the key points and advantages of GPS is its accuracy. Levels of GPS accuracy are extremely high, even for civilian use GPS units. It is also worth defining the difference between accuracy and precision. 



GPS accuracy: The accuracy refers to the degree of closeness the indicated readings are to the actual position. GPS precision: Is the degree to which the readings can be made. The smaller the circle of unknown the higher the precision.

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The accuracy obtained in this way depends mainly on the:  Quality of the reference receiver

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 

Quality of the user's receiver Update rate and data latency (communications bandwidth)  Distance from reference to user  Multipath at the reference receiver  Multipath at the user's site Recently, the smart phones (Android, Black berry and iPhone) come furnished with A-GPS technology which provides the spatial coordinates of the user location with the combination of Global Positioning System (GPS) satellites data with support from cellular network and it works indoor and outdoor, responds faster, and uses less battery power. 2.2 Assisted-GPS Assisted GPS, also known as A-GPS or AGPS is a system that improves the startup performance, or time-tofirst-fix (TTFF), of a GPS satellite-based positioning system. In AGPS, the Network Operator deploys an AGPS server. These AGPS servers download the orbital information from the satellite and store it in the database. An AGPS capable device can connect to these servers and download this information using Mobile Network radio bearers such as GSM, CDMA, WCDMA, and LTE or even using other wireless radio bearers such as Wi-Fi. Generally, the data rate of these bearers is high; hence downloading orbital information takes less time.

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takes longer to establish connectivity with 4 satellites. AGPS system costs money to use A-GPS devices on an ongoing basis because they use mobile network resources. GPS devices communicate directly with satellites for free. There is no cost of operation once the device is paid for.

Figure.2.3: Difference between Standard GPS and AGPS GPS is real-time solution provider whereas AGPS is not. The network usage is required every time we move out of the service area. It is useful only for locating a particular place in small area. There is no privacy in GPS and AGPS since the Assistance server knows the location of the device. There needs to be communication over the wireless for processing of GPS information so this could be expensive. III. LBS COMPONENTS

Figure.2.2: Architecture of A-GPS System It deals signal and wireless network problems by using assistance from other services. Such a technology in our smart phones can aid in different ways like tracking current location, getting turn-by-turn direction instructions, route tracking, etc. 2.3 The Difference Between Autonomous GPS and Assisted- GPS The major difference between both systems is speed and cost. A-GPS devices determine location coordinates faster because they have better connectivity with cell sites than directly with satellites whereas GPS devices may take several minutes to determine their location because it

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Most of Location Based Services need several components. I have suggested the model of “5+1” components of LBS – five technological and 1 human related: 1. Positioning systems – allow geographically localizing the mobile device both outdoor and indoor using: satellite-based systems, Cell-ID, RFID, Bluetooth, WiMax, and Wireless LANs. 2. Communication Network – the wireless network that allows for transfer of data between user (thought mobile device) and server (service provider). Nowadays it is in most cases wireless internet (e.g. GPRS, 3G, and 4G). 3. Service and Application Provider – the LBS provider, including the software (e.g. GIS) and other distributed services and components that are used to resolve the query and provide the tailored response to the user. 4. Data and Content Provider – service providers will usually not store and maintain all the information, which can be requested by users. Therefore geographic base data and location information data will be usually requested from the maintaining authority or business and industry partners.

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3.1 METHODOLOGY

Figure.3.1: Components of LBS 5.

Mobile Devices – any portable device that has capabilities to utilize stated above components of LBS, for example: mobile phones (including smart phones), tablets, palmtops, personal navigation devices, laptops etc. User – operator of the mobile device and the person that is utilizing potential of modern mobile device and infrastructures in order to get value added information or entertainment.

Two methodologies used to implement LBS• To process location data in a server and to promote the generated response to the clients. • To find location data for a mobile device-based application that can use it directly. To discover the position of the mobile, LBS must use positioning methods in real time. The accuracy of the methodology depends on the approach used. Locations can be represented in spatial terms or as text descriptions. A spatial location can be represented in the used latitude-longitude-altitude coordinate system. Latitude is defined as 0-90 degrees north or south of the equator and longitude as 0-180 degrees east or west of the prime meridian, that passes through the Greenwich, England. Altitude is represented in meters above sea level. A text description is usually defined as a street location, including city, pin code. The location of the device can be retrieved by, i) Mobile Phone Service Provider NetworkThe current cell ID is used to locate the Base Transceiver Station (BTS) that the mobile phone is interacting with and the location of that BTS. It is the most basic and cheapest method for this purpose. A GSM cell may be anywhere from 2 to 20 kilometers in diameter. Other approaches used along with cell ID can achieve location granularity within 150 meters. ii) Satellites The Global Positioning System (GPS) uses 24 satellites orbiting the earth. It finds the user position by calculating differences in the times the signals, from different satellites. GPS are in-built with the smart phones. Assisted-GPS (A-GPS) is the new technology for smart phones that integrates the mobile network with the GPS to give a better accuracy of 5 to 10 meters. This fixes the position within seconds, has better coverage and consumes less battery power and requires fewer satellites. IV. ANDROID APPLICATION: WORKING WITH USE OF GPS, GOOGLE MAPS API

Figure.3.2: LBS Components and Service Process Figure-3.2 shows the connections between these components, and the process of a LBS service. First, user sends a service request using the application running on mobile device (Step 1). The service request, with user's current location information received from the positioning component (in this example, GPS data), is sent to service server via the mobile communication network (Step 2). The service server requests geographic database and other associated database to gain needed information (Step 3, 4). At last, the requested information is sent back to user's mobile phone via mobile communication network paragraphs must be indented.

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It is the biggest and most important part of the entire application. It uses Android SDK API to manage the GPS Sensor, Google Maps API to show the Map powered by Google Maps, to display the markers about events on the Map. Knowing where the user is allows your application to be smarter and deliver better information to the user. When developing a location-aware application for Android, you can utilize GPS and Android's Network Location Provider to acquire the user location. Although GPS is most accurate, it only works outdoors; it quickly consumes battery power, and doesn't return the location as quickly as users want. Android's Network Location Provider determines user location using cell tower and Wi-Fi signals, providing location information in a way that works indoors and outdoors, responds faster, and uses less battery power. To obtain the user location in your

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application, you can use both GPS and the Network Location Provider, or just one.  Challenges in Determining User Location There are several reasons why a location reading (regardless of the source) can contain errors and be inaccurate. Some sources of error in the user location include:  Multitude of location sources - GPS, Cell-ID, and Wi-Fi can each provide a clue to user’s location. Determining which to use and trust is a matter of tradeoffs in accuracy, speed, and battery-efficiency.  User movement - Because the user location changes, you must account for movement by re-estimating user location every so often.  Varying accuracy - Location estimates coming from each location source are not consistent in their accuracy. A location obtained 10 seconds ago from one source might be more accurate than the newest location from another or same source. 4.1 ANDROID LOCATION API Android also provide an API to access the Google maps. So with the help of the Google maps and the location APIs the application can show required places to the user on the map. 4.2 GOOGLE PLACES API On 10 May, 2011, at the Google I/O developer Conference in San Francisco, Google announced the opening up and general availability of the Google Places API. The Google Places API is a service that returns data about Places — defined within this Web Service as, spatial locations, or preferred points of interest — using HTTP requests. Place response specifies locations as latitude/longitude coordinates. The four types of requests are available with the Google Places API- There are 4 fundamental Place services available: o Place Searches - It returns an array of nearby Places based on a location defined by the user. o Place Details - It returns more specific data about a user defined Place. o Place Check-ins - Check-ins is used to gauge a Place's popularity; frequent check-ins will boost a Place's priority in application's Place Search responses. o Place Reports - It allows the users to add new locations to the Place service, and to delete Places that the application has added to the database. V. PROPOSED SYSTEM Proposal of an integrated android application is based on location information.

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In the proposed system, we are going to track the location of a user with the help of the device’s location services. This does not require a user to have a sim card to be mandatory (as we are not tracking based on the signal). The user can easily tag his/her location with the help of WIFI (if available). The user (admin) can then view the current location of particular person with their posted comments and time this information must be available in android mobile device and also in user personalized format.  PROCESS OF PROPOSED APP Users are requested to login in the app. This is only for security purpose. Two or more user details (user name, password) will be stored in the database. User logs in to the app. If the user is unauthorized or the username and password is incorrect, then the alert message will be displayed. The app open with main page that will have a text box (to type something), and a “tag” button. When the user taps the button, his current location will be gathered with the help of his mobile device’s location services. If the mobile’s location services had not been enabled, the app will show an alert message saying “Please Enable Location Services”. If enabled, his current location will be stored in the database with his name. The users can logout of the application. Figure 5.1 shows this scenario.

Figure.5.1: User Scenario When the admin wants to know the current location of User, then the admin logs in, his main page will contain a “map” button. On tapping the button, Google maps will be generated with the help of Google maps API. The map will contain the User’s tags with his comments (if any). The following figure 5.2 shows this scenario.

5.1 IMPLEMENTATION OF PROPOSED SYSTEM

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mobile device with the user customized format, then it’s helpful to manage their valuable time effectively and efficiently. VII. FUTURE SCOPE Yet now we can manage limited number of users identity which is visualization of user location, this will be overcome by means of fetching separate server for gathering user’s information by launching this, we can break the limitation which was occurred in previous task. So my future research will be able to implement the any number user’s identity. And this any number of users information will also be grouped according to the nature of role they performing; it should be achieved by using filtering mechanism. Figure.5.2: Admin Scenario

REFERENCES

This application is mainly focused to design for marketing field. For example, sales executives or sales representatives tag their location at each point; it will be viewed by their sales manager, if he wants to monitor their team members or sales executives. VI. CONCLUSION Android System provides the opportunity to determine the current geographical location and to build location-aware applications, without focusing on the details of the underlying location technology. To obtain the user location, we can use one of:  

GPS Provider Android’s Network Location Provider (availability of cell tower and Wi-Fi access points)

or both of them. Every provider has its cons and pros, and can be used depending on the circumstances at each situation. The use of Location Services is, in order to get the current location, by choosing the best provider at each time. In this paper, we developed the LBS for people with ease of their communication usage through Android mobile. Once you learn about the location-related APIs and capabilities that the Android platform provides, you can use them to create the next great location aware application. If all the information must be available on a

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[1] Amit Kushwaha, Vineet Kushwaha, ”Location Based Services using Android Mobile Operating System”, IJAET, Vol. 1,Issue 1,pp.14-20, Mar. 2011. [2] Prof. Seema Vanjire, Unmesh Kanchan, Ganesh Shitole, Pradnyesh Patil,”Location Based Services on Smart Phone through the Android Application”, IJARCCE, Vol. 3, Issue 1, Jan. 2014. [3] Manav Singhal, Anupam Shukla, ”Implementation of Location Based Services in Android using GPS and Web services”, IJCSI, Vol. 9, Issue 1, No 2, Jan. 2012 [4] Bhupinder S. Mongia Vijay K. Madisetti, Fellow, IEEE, “Reliable Real-Time Applications on Android OS”, submitted for publication-June 18, 2010. [5] [Online]:http://www.smashingmagazine.com/201 3/11/22/four-ways-to-build-a-mobile-app-part1native-ios/ [6] [Online]:http://www.sencha.com/products/touch [7] [Online]:file:///F:/gps/Autonomous GPS, Assisted GPS or AFLT What and Why-BI BlogBIBlog.htm [8] [Online]:file:///F:/gps/GPS Accuracy, Errors & Precision Radio-Electronics.Com.htm [9] [Online]:file:///F:/gps/GPS Accuracy Levels.htm [10] [Online]:http://geoawesomeness.com/knowledge -base/location-based-services/location-basedservices-components/

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Performance Analysis of Discrete Cosine Transform based image compression S.VIJAYARAGHAVAN1, M.A.ARCHANA2, Dr.C.PARTHASARATHY3 1, 2 Research Scholars, 3 Assistant Professor-II, SCSVMV University. professorvijayece@gmail.com, maarchaname@gmail.com, drsarathy45@gmail.com ABSTRACT Image compression is one of the most important criteria in multimedia applications. Compression allows efficient utilization of channel bandwidth and storage size. Typical access speeds for storage mediums are inversely proportional to capacity. Through data compression, such tasks can be optimized. Image compression is a part of that data compression. The discrete cosine transform (DCT) is a technique for converting a signal into elementary frequency components. Here we develop some simple functions to compute the DCT and to compress images. Different images are taken for compression using DCT and the performance parameters are analyzed using Mat lab. Image Compression is studied using 2-D discrete Cosine Transform. The original image is transformed in different window sizes. The implementation of this work was successful on achieving significant PSNR values. Keywords: Discrete Cosine Transform, Pixels, Bit Rate, Mean Square Error, Signal to Noise Ratio, PSNR

information. The basic objective of image compression is to find an image representation in which pixels are less correlated. The two fundamental principles used in image compression are redundancy and irrelevancy. Redundancy removes redundancy from the signal source and irrelevancy omits pixel values which are not noticeable by human eye. JPEG and JPEG 2000 are two important techniques used for image compression. Work on international standards for image compression started in the late 1970s with the CCITT (currently ITU-T) need to standardize binary image compression algorithms for Group 3 facsimile communications. Since then, many other committees and standards have been formed to produce de jure standards (such as JPEG), while several commercially successful initiatives have effectively become de facto standards (such as GIF). Image compression standards bring about many benefits, such as: (1) easier exchange of image files between different devices and applications; (2) reuse of existing hardware and software for a wider array of products; (3) existence of benchmarks and reference data sets for new and alternative developments

INTRODUCTION Image compression is very important for efficient transmission and storage of images. Demand for communication of multimedia data through the telecommunications network and accessing the multimedia data through Internet is growing explosively. With the use of digital cameras, requirements for storage, manipulation, and transfer of digital images, has grown explosively. These image files can be very large and can occupy a lot of memory. A gray scale image that is 256 x 256 pixels has 65, 536 elements to store, and a a typical 640 x 480 color image has nearly a million. Downloading of these files from internet can be very time consuming task. Image data comprise of a significant portion of the multimedia data and they occupy the major portion of the communication bandwidth for multimedia communication. Therefore development of efficient techniques for image compression has become quite necessary. A common characteristic of most images is that the neighboring pixels are highly correlated and therefore contain highly redundant

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IMAGE COMPRESSION The need for image compression becomes apparent when number of bits per image is computed resulting from typical sampling rates and quantization methods. For example, the amount of storage required for given images is (i) a low resolution, TV quality, color video image which has 512 x 512 pixels/color,8 bits/pixel, and 3 colors approximately consists of 6 x 10⁶ bits;(ii) a 24 x 36 mm negative photograph scanned at 12 x 10⁻⁶mm:3000 x 2000 pixels/color, 8 bits/pixel, and 3 colors nearly contains 144 x 10⁶ bits; (3) a 14 x 17 inch radiograph scanned at 70 x 10⁻⁶mm: 5000 x 6000 pixels, 12 bits/pixel nearly contains 360 x 10⁶ bits. Thus storage of even a few images could cause a problem. As another example of the need for image compression, consider the transmission of low resolution 512 x 512 x 8 bits/pixel x 3-color video image over telephone lines. Using a 96000 bauds (bits/sec) modem, the transmission would take approximately 11 minutes for just a single image, which is unacceptable for most applications.

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Figure 1 Block Diagram of Image Compression Principle Number of bits required to represent the information in an image can be minimized by removing the redundancy present in it. There are three types of redundancies: (i) Spatial redundancy, which is due to the correlation or dependence between neighboring pixel values. (ii) Spectral redundancy, which is due to the correlation between different color planes or spectral bands. (iii) Temporal redundancy, which is present because of correlation between different frames in images. Image compression research aims to reduce the number of bits required to represent an image by removing the spatial and spectral redundancies as much as possible. Data redundancy is of central issue in digital image compression. If n1 and n2 denote the number of information carrying units in original and compressed image respectively ,then the compression ratio CR can be defined as CR=n1/n2;And relative data redundancy RD of the original image can be defined as RD=1-1/CR; Three possibilities arise here: (1) If n1=n2, then CR=1 and hence RD=0 which implies that original image do not contain any redundancy between the pixels. (2) If n1>>n1, then CR→∞ and hence RD>1 which implies considerable amount of redundancy in the original image. (3) If n1<<n2, then CR>0 and hence RD→-∞ which indicates that the compressed image contains more data than original image. Types of compression Lossless versus Lossy compression: In lossless compression schemes, the reconstructed image, after compression, is numerically identical to the original image.

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However lossless compression can only a achieve a modest amount of compression. Lossless compression is preferred for archival purposes and often medical imaging, technical drawings, clip art or comics. This is because lossy compression methods, especially when used at low bit rates, introduce compression artifacts. An image reconstructed following lossy compression contains degradation relative to the original. Often this is because the compression scheme completely discards redundant information. However, lossy schemes are capable of achieving much higher compression. Lossy methods are especially suitable for natural images such as photos in applications where minor (sometimes imperceptible) loss of fidelity is acceptable to achieve a substantial reduction in bit rate. The lossy compression that produces imperceptible differences can be called visually lossless. Predictive versus Transform coding: In predictive coding, information already sent or available is used to predict future values, and the difference is coded. Since this is done in the image or spatial domain, it is relatively simple to implement and is readily adapted to local image characteristics. Differential Pulse Code Modulation (DPCM) is one particular example of predictive coding. Transform coding, on the other hand, first transforms the image from its spatial domain representation to a different type of representation using some well-known transform and then codes the transformed values (coefficients). This method provides greater data compression compared to predictive methods, although at the expense of greater DISCRETE COSINE TRANSFORM BASED IMAGE COMPRESSION Discrete Cosine Transform (DCT) exploits cosine functions, it transform a signal from spatial representation into frequency domain. The DCT represents an image as a sum of sinusoids of varying magnitudes and frequencies. DCT has the property that, for a typical image most of the visually significant information about an image is concentrated in just few coefficients of DCT. After the computation of DCT coefficients, they are normalized according to a quantization table with different scales provided by the JPEG standard computed by psycho visual evidence. Selection of quantization table affects the entropy and compression ratio. The value of quantization is inversely proportional to quality of reconstructed image, better mean square error and better compression ratio. In a lossy compression technique, during a step called Quantization, the less important frequencies are discarded, then the most important frequencies that remain are used to retrieve the image in decomposition process. After quantization, quantized coefficients are rearranged in a zigzag order for further compressed by an efficient lossy coding algorithm.

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Let us present here briefly the computation technique for DCT’s of an image. The definition of DCT for a 2D images x (m,n) of size NxN is as follows:

C k , l   m0 n0 4 xm, n  cos 2 m2K1k cos 2 n2N1l  N 1

N 1

0  k, l  N  1 e low-low sub band xLL (m,n) of the image be obtained as:

x LL ( m , n ) 

1 4

{ x ( 2 m , 2 n )  x ( 2 m  1, 2 n )

 ( 2 m , 2 n  1)  x ( 2 m  1, 2 n  1 )}, 0  m,n 

N 2

Figure 2 BUILDING- original image

 1.

Let CLL (k,l), 0 < k,l < N/2-1 be the 2D DCT of xLL(m,n). Then the sub band approximation of DCT of x(m,n) is given by:

4cos(2Nk ) cos(2Nl )CLL (k, l), k, l  0,1,......,N2 1 C(k,l)   0, otherwise  It may be noted that depending upon the definition of DCT, sub band DCT’s are multiplied by a factor (in this

 k   l   cos  ). The definition of inverse  2N   2N 

case 4 cos

Figure 3 BUILDING- Gray scale image

DCT (IDCT) should also be modified accordingly. We refer this as sub band approximation of DCT as k , l  0 ,1 ,......, N2  1  4 C LL ( k , l ), C (k , l)   0, otherwise  We refer this approximation as the low-pass truncated approximation of DCT. Interestingly, the multiplication factor 4 appears due to the definition of DCT used in this work. However, this factor does not have any effect in the final results obtained by them (PSNR values of downsized (halved) and then upsized. While halving an image, DCT coefficients for N/2-point DCT are obtained by dividing the N-point DCT coefficients.

Figure 4 BUILDING- DCT image

EXPERIMENTAL RESULTS Experimentations are carried out for studying the performances of the three different images compressed at different levels. In the context of the JPEG compression, the effect of quantization on the approximated coefficients during image-halving or image-doubling should be observed here. The PSNR values for different compression levels for the Building, BMW car, and Peacock images were plotted in Figures as shown below. The performance of Bit Rate, Mean Square Error, Signal to Noise Ratio, PSNR values for the images is also tabulated.

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Figure 5 BMW CAR- original image

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Figure 6 BMW CAR- Gray scale image

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Figure 10 PEACOCKâ&#x20AC;&#x201D;DCT Image 200 150

PEACOCK

100

BMW CAR

BUILDING

0 0.5

0.75

Figure 7 BMW CAR - DCT image Figure 11 Bit rate (bps) vs. PSNR (dB) for DCT based image compression of Peacock, BMW car and Buildings images TABLE I - Performance Analysis

Image

Figure 8 PEACOCK- original image Building

BMW Car

Figure 9 PEACOCK- Gray scale image Peacock

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Bit Rate (bps)

Mean Square Error

Signal To Noise Ratio (db)

PSNR(db)

0.5 0.75 1 2 4 0.5 0.75 1 2 4 0.5 0.75 1 2 4

114.6 60.9 47.9 6.6 0.2 36.5 175.9 124.6 30.8 0.9 302.2 232.2 164.5 33.9 2.5

13.7 16.4 17.5 26.1 42.4 14.1 15.4 16.9 23.0 38.6 9.4 10.5 12.0 18.9 30.2

27.5 30.3 31.3 39.9 56.2 24.4 25.7 27.2 33.2 48.8 23.3 24.5 26.0 32.8 44.2

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CONCLUSION [9]

DCT based Image compression transform is an efficient technique for obtaining better quality of image in multimedia applications. The Performance analysis of three different images illustrates that the PSNR value varies for different bit rates and it also shows that there is a better performance of mean square error and for various bit rate. The outputs were obtained using MATLAB 8. The future of this is that it can be implemented using FPGA.

NageswaraRaoThota, Srinivasa Kumar Devireddy. “Image Compression Using Discrete Cosine Transform” Georgian Electronic Scientific Journal: Computer Science and Telecommunications 3 (2008). [10] Saraswathy, K., D. Vaithiyanathan, and R. Seshasayanan. “A DCT approximation with low complexity for image compression” Communications and Signal Processing (ICCSP), 2013 International Conference on. IEEE, 2013.

REFERENCES [1] A. M. Shams, a. Chidanandan, w. Pan, and m. A.Bayoumi, “NEDA: A LowPower High-PerformanceDCT rchitecture,” IEEE trans. Signal process. vol.54, no. 3, pp. 955–964, mar. 2006. [2] M. R. M. Rizk and m. Ammar, “Low Power Small Area High Performance 2D-Dct Architecture,” in proc. Int. Design test workshop, 2007, pp. 120–125. [3] C. Peng, X. Cao, D. Yu, and X. Zhang, “A 250 MHz Optimized D is tr i bu t ed A r c h i t e c t u r e O f 2 D 8 x 8 D C T ,” in Proc. Int. Conf. ASIC, 2007, pp. 189–192. [4] Shinsuke Kobayushi, Kenturo Mita Graduate S c h o o l of Engineering Science, “Rapid prototyping of jpeg encoder using the asip development systempeas-111” Osaka University 0-7803-7663. [5] L.V. Agostini, I.S. Silva, and S. Bampi. Pipelined fast 2d DCT architecture for JPEG image compression. In Integrated Circuits and Systems Design, 2001, 14th Symposium on, pages 226–231, Pireno polis, Brazil, 2001. [6] Yun-Lung Lee, Jun-Wei Yang, and Jer Min Jou Design of a Distributed “JPEG Encoder on a Scalable NoC Platform” Department of Electrical Engineering, National Cheng Kung University, No.1, University Road, Tainan, Taiwan, R.O.C. 978-14244-1617-2/08/S25.00 ©2008IEEE. [7] Telagarapu, Prabhakar, et al. “Image Compression Using DCT and Wavelet Transformations” International Journal of Signal Processing, Image Processing and Pattern Recognition 4.3 (2011). [8] Elamaran, V., and A. Praveen. “Comparison of DCT and wavelets in image coding” Computer Communication and Informatics (ICCCI), 2012 International Conference on. IEEE, 2012.

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The Worldâ&#x20AC;&#x2122;s Smallest Computer for Programmers and App Developers (Raspberry Pi) N.Abirami1, V.Goutham2 1

Assistant Professor, Computer Science & Engineering,

Sree Sastha Institute of Engineering and Technology, Chennai. abi.profession@gmail.com 2

Student, B.E.(CSE) V-Semester, Computer Science & Engineering, Sree Sastha Institute of Engineering and Technology, Chennai. gouthamvenkatesh95@gmail.com

Abstractâ&#x20AC;&#x201D; The Raspberry Pi (RasPi) is an ultra-low-cost, singleboard, credit-card sized Linux computer which was conceived with the primary goal of teaching computer programming to children. It was developed by the Raspberry Pi Foundation, which is a UK registered charity. The foundation exists to promote the study of computer science and related topics, especially at school level, and to put the fun back into learning computing. The device is expected to have many other applications both in the developed and the developing world. Raspberry-Pi is manufactured and sold in partnership with the world-wide industrial distributors Premier Farnell/Element 14 and RS Components Company. The Raspberry Pi has a Broadcom BCM2835 system on chip which includes an ARM1176JZF- S 700 MHz processor, Video Core IV GPU, and 256 megabytes of RAM. It does not include a built-in hard disk or solid-state drive, but uses an SD card for booting and long-term storage. The Foundation provides Debian and Arch Linux ARM distributions for download. Also planned are tools for supporting Python as the main programming language, with support for BBC BASIC, C and Perl. The gadget looks rather odd next to sleek modern offerings such as the iPad, and appears to have more in common with the crystal radio sets of the 1950s. However, the machine is a fullyfledged computer and can be connected to a monitor, keyboard and mouse, as well as speakers and printers.

Rob Dudley of The Raspberry Pi Foundation designed this little board here, the Raspberry Pi, to address a lost generation of computer programmers and hardware engineers. So, this little board here is low cost, it's easily accessible, it's very simple to use. When you power it up you get a nice little desktop environment, it includes all of the things that you need to do to get started to learn programming. There's lots of information out there on the internet that you can take away and start programming code in to make things happen. The great thing about these boards as well is in addition to software, you can play with hardware. So these little general purpose pins here allow access to the processor and you can hang off little hardware projects that you build and you can control via the code you are writing through the software application. So, this is a great tool for kids to learn how computers work at a grassroots level. II.What is a Raspberry Pi?

Fig1 : Raspberry Pi Module

I. INTRODUCTION

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The Raspberry Pi is a credit-card sized computer that plugs into TV and a keyboard. It is a capable little PC which can be used for many of the things that your desktop PC does, like spreadsheets, wordprocessing and games. It also plays high-definition video. A Raspberry -Pi leads, a power supply or SD cards that are not included but can be purchased later. One can buy preloaded SD cards too. The Raspberry Pi measures 85.60mm x 53.98mm x 17mm, with a little overlap for the SD card and

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connectors which project over the edges. It weighs around 45g. Overall real world performance is something like a 300MHz Pentium 2. Raspberry-Pi cannot boot without an SD card.The Raspberry Pi uses Linux kernel-based operating systems. Raspbian, a Debian-based free operating system optimized for the Raspberry Pi hardware, is the current recommended system.The GPU hardware is accessed via firmware image which is loaded into the GPU at boot time from the SD-card. The firmware image is known as the binary blob, while the associated Linux drivers are closed source. Application software use calls to closed source runtime libraries which in turn calls an open source driver inside the Linux kernel. The API of the kernel driver is specific for these closed libraries. Video applications use Open MAX.There are a number of operating systems running, ported or in the process of being ported to Raspberry-Pi. Like, AROS, Android 4.0,Arch Linux ARM, Debian Squeeze, Firefox OS etc.

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ask the user for time information at boot time to get access to time and date for file time and date stamping. However, a real-time clock (such as the DS1307) with battery backup can be added via the IC interface. Hardware accelerated video (H.264) encoding became available on 24 August 2012 when it became known that the existing license also covered encoding. Previously it was thought that encoding would be added with the release of the announced camera module. However, no stable software support exists for hardware H.264 encoding .The New Raspberry Pi model B's would be fitted with 512 MB instead of 256 MB RAM.

Fig4: Internals of Raspberry Pi POWER 5v micro USB connector There has been a lot of speculation about the power supply design for the production Raspberry Pi devices. The alpha boards use a pair of switchmode power supplies to generate 5V and 3V3 rails from a 6-20V input on a coaxial jack, and LDOs to generate the low-current 2V5 and 1V8 rails for the analog TV DAC and various I/O functions.

Fig 2: Raspberry Pi Board III. Whatâ&#x20AC;&#x2122;s the filling of a raspberry pi? Initial sales were of the Model B, with Model A following in early 2013. Model A has one USB port and no Ethernet controller, and costs less than the Model B with two USB ports and a 10/100 Ethernet controller or the B+ with four USB ports. Though the Model A does not have an 8P8C (RJ45) Ethernet port, it can connect to a network by using an external user-supplied USB Ethernet or Wi-Fi adapter. On the model B the Ethernet port is provided by a built-in USB Ethernet adapter. As is typical of modern computers, generic USB keyboards and mice are compatible with the Raspberry Pi. The Raspberry Pi does not come with a real-time clock, so an OS must use a network time server, or

ISBN NO : 978 - 1502893314

Fig 3: Power Audio/Video 1) RCA

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An RCA connector, sometimes called a phono connector or cinch connector, is a type of electrical connector commonly used to carry audio and video signals. The connectors are also sometimes casually referred to as A/V jacks. The name "RCA" derives from the Radio Corporation of America, which introduced the design by the early 1940s for internal connection of the pickup to the chassis in home radio-phonograph consoles. It was originally a lowcost, simple design, intended only for mating and disconnection when servicing the console. Refinement came with later designs, although they remained compatible.

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communication, and power supply between computers and electronic devices.USB was designed to standardize the connection of computer peripherals (including keyboards, pointing devices, digital cameras, printers, portable media players, disk drives and network adapters) to personal computers, both to communicate and to supply electric power.

2)ETHERNET In computer networking, Fast Ethernet is a collective term for a number of Ethernet standards that carry traffic at the nominal rate of 100 Mbit/s, against the original Ethernet speed of 10 Mbit/s. Of 2)HDMI the Fast Ethernet standards 100BASE-TX is by far HDMI (High-Definition Multimedia Interface) is the most common and is supported by the vast a compact audio/video interface for transferring majority of Ethernet hardware currently produced. uncompressed video data and compressed or Fast Ethernet was introduced in 1995 and remained uncompressed digital audio data from an HDMI- the fastest version of Ethernet for three years before compliant source device, such as a display being superseded by gigabit Ethernet. controller, to a compatible computer monitor, video 3)GPIO projector, digital television, ordigital audio device. General-purpose input/output ( GPIO) is a HDMI is a digital replacement for existing analog generic pin on an integrated circuit whose behavior, video standards. including whether it is an input or output pin, can be controlled by the user at run time.GPIO pins 3) 3.5 mm Personal computer sound cards use a 3.5 mm have no special purpose defined, and go unused by phone connector as a mono microphone input, and default. The idea is that sometimes the system deliver a 5 V polarizing voltage on the ring to integrator building a full system that uses the chip power electret microphones. Compatibility between might find it useful to have a handful of additional digital control lines, and having these available different manufacturers is unreliable. from the chip can save the hassle of having to arrange additional circuitry to provide them.

Fig5: Audio/Video CONNECTIVITY 1)USB Universal Serial Bus (USB) is an industry standard developed in the mid-1990s that defines the cables, connectors and communications protocols used in a bus for connection,

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Fig6: Connectivity INTERNALS 1) SOC

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A system on a chip or system on chip (SoC or SOC) is an integrated circuit(IC) that integrates all components of a computer or other electronic system into a single chip. It may contain digital, analog, mixed-signal, and often radio-frequency functionsâ&#x20AC;&#x201D;all on a single chip substrate. The contrast with a microcontroller is one of degree. Microcontrollers typically have under 100 kB of RAM (often just a few kilobytes) and often really are single-chip-systems, whereas the term SoC is typically used for more powerful processors, capable of running software such as the desktop versions of Windows and Linux, which need external memory chips (flash, RAM) to be useful, and which are used with various external peripherals.

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image sensor interfaces and provides a standard output that can be used for subsequent image processing.A typical Camera Interface would support at least a parallel interface although these days many camera interfaces are beginning to support the MIPI CSI interface.The Raspberry Pi Foundation has released their Pi compatible camera module that connects to the CSI. It is a 5 megapixel camera with a fixed focused lens. 5) DSI The display serial interface, or DSI as I will refer to it from now on, is a high speed serial connector located between the power connector and the GPIO header on the Raspberry Pi. The purpose of the DSI connector is to give the end user a quick and easy way to connect an LCD panel to the Pi. In this case the chip being interfaced with is the Broadcom BCM2835, which is at the heart of the Raspberry Pi.

2)LAN A wireless LAN controller is used in combination with the Lightweight Access Point Protocol (LWAPP) to manage light-weight access points in large quantities by the network administrator or network operations center. The wireless LAN controller is part of the Data Plane within the Cisco Wireless Model. The WLAN controller automatically handles the configuration of wireless Fig7: Internals access-points. STORAGE 3) JTAG SD The JTAG headers on the Raspberry Pi are Secure Digital (SD) is a non-volatile memory located near the audio jack. They are labeled P2 and card format for use in portable devices, such as P3. JTAG stands for Joint Test Action Group. mobile phones, digital cameras. Headers or pins with the JTAG label are mainly used for debugging during the development of embedded software and hardware.JTAG header P2 is connected to the Broadcom BCM2835. As you may suspect from what I said about the DSI, It is all closed source and there is virtually no way to use this header. It is not a JTAG interface for the ARM CPU like so many people always assume.JTAG header P3 is connected to the LAN9512 LAN and USB Hub chip. It is only on the model B Pi since Fig 8: Storage the model A does not use the LAN9512. The LAN9512 is a USB 2.0 bus and 10/100 ethernet controller. A CONFESSION 4) CSI IV.Uses Of Raspberry Pi The CAMIF, also the Camera Interface block is the hardware block that interfaces with different

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10.LIBRE OFFICE LibreOffice is a free and open source office suite, developed by The Document Foundation. It was forked from OpenOffice.org in 2010, which was an open-sourced version of the earlier StarOffice. The LibreOffice suite comprises programs to do word processing, spreadsheets, slideshows, diagrams and drawings, maintain databases, and compose math formulae. LibreOffice uses the international ISO/IEC standard OpenDocument file format as its native format to save documents for all of its applications (as do its OpenOffice.org cousins Apache OpenOffice and NeoOffice).

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a range of educational and entertainment constructivist purposes from math and science projects, including simulations and visualizations of experiments, recording lectures with animated presentations, to social sciences animated stories, and interactive art and music. Simple games may be made with it, as well. Viewing the existing projects available on the Scratch website, or modifying and testing any modification without saving it requires no online registration.

Fig 10: Python

8.GAME CONSOLE

Fig 9: LibreOffice 9.PROGRAMMING

A video game console is a device that outputs a video signal to display a video game. The term "video game console" is used to distinguish a machine designed for consumers to use for playing video games on a separate television in contrast to arcade machines, handheld game consoles, or home computers.

Python Python is a widely used general-purpose, highlevel programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than would be possible in languages such as C. The language provides constructs intended to enable clear programs on both a small and large scale. Python supports multiple programming Fig 11:Game console paradigms, including object-oriented, imperative and functional programming or procedural styles. It 7.MINECRAFT features a dynamic type system and automatic memory management and has a large and Minecraft is a sandbox indie game originally comprehensive standard library. created by Swedish programmer Markus "Notch" Persson and later developed and published by SCRATCH Mojang. It was publicly released for the PC on May Scratch is a multimedia authoring tool that can be 17, 2009, as a developmental alpha version and, used by students, scholars, teachers, and parents for after gradual updates, was published as a full

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release version on November 18, 2011. A version for Android was released a month earlier on October 7, and an iOS version was released on November 17, 2011. On May 9, 2012, the game was released on Xbox 360 as an Xbox Live Arcade game, as well as on the PlayStation 3 on December 17, 2013. Both console editions are being codeveloped by 4J Studios. All versions of Minecraft receive periodic updates.

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photo, audio playback, and sometimes video recording functionality. An HTPC system typically has a remote control and the software interface normally has a 10-foot user interface design so that it can be comfortably viewed at typical television viewing distances. An HTPC can be purchased preconfigured with the required hardware and software needed to add video programming or music to the PC. Enthusiasts can also piece together a system out of discrete components as part of a software-based

Fig 12: Minecraft 6.TOR ROUTER

HTPC.

Tor (previously an acronym for The Onion Router) is free software for enabling online anonymity and resisting censorship The term "onion routing" refers to application layers of encryption, nested like the layers of an onion, used to anonymize communication The NSA(National Security Agency) has a technique that targets outdated Firefox browsers codenamed EgotisticalGiraffe,and targets Tor users in general for close monitoring under its XKeyscore program.

Fig 14: HTPC 4. Bartender A robotic drink-dispensing rig is aiming to steal your customers while pouring cocktail creations at the push of a touchscreen button. Its creators call it Bartendro. Operated through an iPad interface, the open source, synthetic Al Swearengen holds up to 15 bottles of beverage plumbed into custom-designed, Raspberry Pi-controlled pumps. Itâ&#x20AC;&#x2122;s capable of mixing dozens of drinks, including black Russians, Kahlua mudslides, or almost any other classy beverage of your choosing. A tiny Raspberry Pi serves as the brain, operating up to 15 dispensers, which essentially suck booze out of whatever bottles youâ&#x20AC;&#x2122;ve got handy, then mix

Fig13: Tor Router 5.HTPC A home theater PC (HTPC) or media center computer is a convergence device that combines some or all the capabilities of a personal computer with a software application that supports video,

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your

specifications.

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check the display size), using the Free Pascal and Lazarus IDE to compile a suitable wall-clock program, learning how to auto-login on the Raspberry Pi, and how to start a program automatically on the desktop (i.e. using the GUI).

Fig 15: Bartender 3.CAMERA Fig 17:Clock The Raspberry Pi camera module can be used to take high-definition video, as well as stills photographs. Itâ&#x20AC;&#x2122;s easy to use for beginners, but has plenty to offer advanced users if youâ&#x20AC;&#x2122;re looking to expand your knowledge. There are lots of examples online of people using it for time-lapse, slowmotion and other video cleverness. You can also use the libraries we bundle with the camera to create effects.The camera module is very popular in home security applications, and in wildlife camera traps.You can also use it to take snapshots.

Fig 16:Camera 2.CLOCK This simple project was to replace a radio clock working from MSF with a clock based on NTP. It just so happened that an older 10.2-inch LCD TV became free, and I wanted to have a go at programming the Raspberry Pi and learn just a little (not too much) more about Linux. The project involved setting up the Raspberry Pi to display correctly on the TV (I converted a Windows Testcard program to run on Linux to

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1.PIBOLT One of the coolest little developer boards out there is the Raspberry Pi. That board can be used for any project needing electronics for control that you can dream up. A new robotics kit made for use with the Raspberry Pi is getting ready to hit Kickstarter. That robotics kit is called the PiBot. PiBot will have a range of features that electronics fans will appreciate including voice recognition, face recognition, and live HD streaming from the PiBot camera. The robot will be controllable from a smartphone and tablet. PiBot will also be able to follow lines, measure distance, and use GPS. The company behind the PiBot also plans to have workshops that will allow people to come in and play with the robotics kit. There are a few things we don't know at this time such as when the PiBot will hit market and how much it will cost.

Fig 18:PiBot

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V.Advantages of the Pi 1. Power consumption - The Pi draws about five to seven watts of electricity. This is about one tenth of what a comparable full-size box can use. Since servers are running constantly night and day, the electrical savings can really add up. 2. No moving parts - The Pi uses an SD card for storage, which is fast and has no moving parts. There are also no fans and other things to worry about. 3. Small form factor - The Pi (with a case) can be held in your hand. A comparable full-size box cannot. This means the Pi can be integrated inside of devices, too. 4. No noise - The Pi is completely silent. 5. Status lights - There are several status lights on the Pi's motherboard. With a clear case you can see NIC activity, disk I/O, power status, etc. 6. Expansion capabilities - There are numerous devices available for the Pi, all at very affordable prices. Everything from an I/O board (GPIO) to a camera. The Pi has two USB ports, however by hooking up a powered USB hub, more devices can be added. 7. Built-in HDMI capable graphics - The display port on the Pi is HDMI and can handle resolutions up to 1920Ă&#x2014;1200, which is nice for making the Pi in to a video player box for example. There are some converters that can convert to VGA for backwards compatibility 8. Affordable - compared to other similar alternatives, the Pi (revision B) offers the best specs for the price, at least that I've found. It is one of the few devices in its class that offers 512 MB of RAM. 9. Huge community support - The Pi has phenomenal community support. Support can be obtained quite easily for the hardware and/or GNU/Linux software that runs on the Pi mainly in user forums, depending on the GNU/Linux distribution used. 10. Overclocking capability - The Pi can be overclocked if there are performance problems with the application used, but it is at the user's risk to do this.

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VI.Drawbacks of the Pi With all of the positive things about the Pi, there are a couple of items that I feel are very minor drawbacks: 1. ARM architecture - While ARM is a highly efficient and low powered architecture, it is not x86 and therefore any binaries that are compiled to run on x86 cannot run on the Pi. The good news is that entire GNU/Linux distributions have been compiled for the ARM architecture and new ones are appearing all of the time. 2. RAM not upgradable - The main components of the Pi are soldered to the motherboard, including the RAM which is 512 MB. This is not a problem though as GNU/Linux can easily run on this. I've found the Pi uses about 100 MB of RAM while running as a small server (this is without running X11). VII.Conclusion Today virtualisation is very popular so some may say that the cost of spinning up a virtual machine is less than running a Raspberry Pi. But, calculate the power consumption for your hypervisor, and weigh out the differences to see which method in fact costs less overall. Sometimes, a physical box or physical segmentation is needed, or avoiding high costs of running a full hypervisor is a factor, and this is where the Pi can step in.

REFERENCES 1.

Wikipedia

2. 3. 4.

Online guidelines regulated by the members of Schneider Electric.( 132 Fairgrounds Road, West Kingston, RI 02892 USA).

Preferred links from www.google.com

Raspbian Technology Services

raspberrypibooks.net/

raspberrypi.org

Raspberry Pi User Guide (2nd Edition)

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12. Raspberry Pi Projects 10.

Raspberry Pi For Dummies

11.

Raspberry Pi Manual: A practical guide to the revolutionary small computer

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13. Some Notes Are Prepared By Myself .

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Enhancing Vehicle to Vehicle Safety Message Transmission Using Randomized Algorithm P.Ashok Ram M.E-Computer Science and Engineering Sree Sowdambika College Of Engineering Aruppukottai Tamilnadu St,India ashok.inaiyam@gmail.com

Abstract— Reliable local information transmission is the primary concern for periodic safety broadcasting in VANETs. We suggest a sublayer in the application layer of the WAVE stack to increase the reliability of safety applications. Our design uses retransmission of network coded safety messages, which significantly improves the overall reliability. It also handles the synchronized collision problem defined in WAVE as well as congestion problem and vehicle-to-vehicle channel loss. We recommend a discrete phase type distribution to model the time transitions of a node state. Based on this model, we derived network coding. Simulated results based on our analysis show that our method performs better than the previous repetition-based algorithms. Keywords—Ad-hoc networks, network architectures and protocols, multiple access techniques, systems and services, quality of service assurance.

INTRODUCTION

VEHICULAR Ad-hoc NETworks (VANETs) have developed as a potential framework for future active safety systems. Wireless Access in Vehicular Environment (WAVE) architecture is presented in the IEEE 1609.0 standard. IEEE 802.11p has been approved as an alternate to IEEE 802.11 standard and specifies the MAC layer enhancements for vehicular environment. The remarkable changes are increased maximum transmission power and reduced channel bandwidth to 10Mhz, which provide a more reliable communication. The IEEE 1609.4 standard also defines some enhancements to the MAC layer to support multi-channel operation. Both IEEE 1609.4and 802.11p are part of the WAVE architecture. Periodic broadcast and its related safety applications are one of the major driving strengths for implementing VANETs[1]. In VANETs, a safety message is periodically generated (10Hz frequency) and broadcasting to one-hop neighbor vehicles. These periodic “heartbeat” messages are the building blocks of many safety applications.

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Mr.V.Ramachandran M.Tech Assistant professor(Computer Science and Engineering) Sree Sowdambika College Of Engineering Aruppukottai Tamilnadu St,India raamchandran1987@gmail.com

IEEE 1609.4 explains how channel coordination is produced for a WAVE device with a single radio[2].The time is divided into 100ms sync intervals. Each sync interval consists of a Service CHannel (SCH) and a Control CHannel (CCH) (Fig. 1). Every 50ms the WAVE device switches to CCH (channel 178). The periodic transmission of Wave Short Messages (WSM) takes place in the CCH intervals. SCH intervals are used for IP packets. Since WAVE devices should be in the very same channel in order to be able to

Fig. 1. IEEE 1609.4 periodic channel switching.

communicate, the channel switching for all nodes is synchronized. The synchronization mechanism is complete with the IEEE 1609.4 standard. The periodic broadcast is shown to perform well for low node densities (less than 10 nodes). In a dense network, however, congestion becomes a serious problem. It can generate an excessive number of collisions and result in unacceptable reliability measures for safety applications. In [3] and [4], the authors have suggested a congestion control mechanism based on the channel existence. The message rate is adjusted in conjunction with the transmission range to alleviate the congestion problem. Other than the message rate control, adaptive control of the contention window size based on the node density is another way to avoid congestion.The congestion problem is also defined in IEEE 1609.4 where many nodes have a newly generated WSM for transmission and they all switch to CCH at the same time (synchronized collision). In this scenario, collision is expected if two nodes pick the same timeslot in the contention window. Naturally, for high node densities the collision probability increases. Aside from the congestion problem, unreliable vehicle-tovehicle channel and channel errors are other concerns for safety applications. In the IEEE 802.11p broadcast mode,

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Proceedings of International Conference on Advancements in Engineering and Technology there is no acknowledgement. Also, unlike the unicast transmissions, there is no rebroadcasting for lost messages. In [5] several repetitions based access schemes are suggesting to guarantee a low message loss probability. Although message repetition improves the reliability, it can potentially aggravate the congestion problem. We already studied the advantage of network coding in safety applications [6].We exhibited, through simulations, that network coding can obviously improve the successful message delivery. In this paper, we extend our previous results through analysis, and suggest a more comprehensive design. We propose a sub-layer in the application layer of the WAVE architecture (Fig. 2). This sub layer handles the periodically produce messages in the application layer to improve the overall reliability of the updated local neighborhood map and cope with the congestion problem and channel loss. Solid arrows in Fig. 2 represent the handshakings between the sublayer and the rest of the networking stack. The dashed arrow represents the timing feedback from the MAC layer over the intermediate layers. Since our sub layer is at the application layer it needs the timing information for synchronization. For example, the synchronization is necessary for the congestion control algorithm in order to transmit in predefined subframes. We study how and when repeating the message can be helpful to achieve more reliability. In our scheme, each node not only can send its own WSM, it can also transmit a random linear combination of already received WSMs to cooperatively help delivering all WSMs. The low-level design and the exact definition of the protocol is beyond the space and scope of this paper, which aims to deal with the problem systematically. The main purpose of this paper is the systematic studies of random linear network coding in the periodic transmit of â&#x20AC;&#x153;heartbeatâ&#x20AC;? messages. Moreover, we introduce a novel method based on the pseudo random number generator to minimize the network coding overhead.This is especially critical for small safety message size. Repetitive safety message rebroadcasting is an efficient way to maximize the reliability; on the other hand congestion is a serious problem in vehicular network. We also show, through simulation, that in a congested network, network coding can substantially minimize the safety message loss probability. Finally, the network coding algorithm is implemented in ns-2 which provides a more realistic simulation framework. II.

RELATED WORKS

The two main components of the suggested sub-layer in this paper are safety message retransmission and the use of network coding for safety message broadcasting. In the following subsections, first we review the earlier work on safety message repetition, and then we discuss some of the previous works on the application of network coding in VANETs.

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Fig. 2. Reliability sub-layer: interfaces with WAVE Short Message Protocol (WSMP), sensors, and safety applications.

We also review the applications of network coding in gossipbased algorithms, which are closely similar to the application in this paper A. Message Rebroadcasting: Repetitive broadcast of safety messages in VANETs were first proposed in [7].When a safety message is produced it should be delivered to neighbors within the message lifetime. The time is slotted and the message life-time is assumed to be time slots L. In IEEE 802.11p, safety messages are only transferred once during a time frame. This is due to the fact that in IEEE 802.11p broadcast mode, there is no retransmission or acknowledgement. . In Synchronized Fixed Repetition (SFR), w time slots are randomly chosen (out of L) for rebroadcasting. In Synchronized Persistent Repetition (SPR) at each time slot a message is transferred with probability p. To limit the number of collisions, Positive Orthogonal Codes (POC) is suggested [8].The retransmission pattern of each node is assigned based on predetermined binary codes. The 1â&#x20AC;&#x2122;s represent the transmitting time slots in the frame. Any pairwise shifted version of two POC code words has limited correlation. This limited correlation has been shown to increase the message delivery ratio by limiting the number of collisions. B. Network coding: In [9], authors have proved that random linear network coding could achieve the multi-cast capacity in a lossy wireless network. The work in [12] has not been suggested for vehicular networks, but is the closest, in terms of the techniques, to our work. This well-known result cannot be extended to the application of network coding in safety message broadcasting in VANETs. In a typical vehicular network, the number of vehicles in one-hop neighborhood does not extend asymptotically. In addition, the analysis in only considers long-term throughput, but for delay sensitive safety messages short-term throughput or the successful message reception in a small time window is of interest. More specifically, we describe an upper bound for the message loss probability in the CCH interval (50ms according to IEEE 1609.4 standard) which cannot be inferred from the analysis.

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Proceedings of International Conference on Advancements in Engineering and Technology 1)Vehicular Networks: Most of the earlier work on the application of network coding in vehicular network deal with the content distribution from a Road Side Unit (RSU) to multiple On Board Units (OBUs) or consider only throughput performance[10] .To the best of our knowledge, there are only a few works on network coding application in safety message transmitting. In [11], Symbol-Level Network Coding (SLNC) is used for multimedia streaming from RSUs to vehicles. In [18], SLNC is utilized for content distribution, in order to maximize the download rate from the access points. SLNC is shown to achieve excellent performance compared to packet level network coding in unicast transmissions. This is effective for large packet sizes. For small safety messages, if each message is split into smaller symbols, the network coding over-head can be compared to the symbol size leading to network inefficiency. To address this drawback, our proposed network coding algorithm does not need any message decomposition. 2) Gossip Algorithms: In the context of gossip algorithms, the problem of diffuse k messages in a large network of n nodes is considered. At each time slot, each node chooses a communication partner in a random uniform fashion and only one message is transmitted, while in the broadcast scenario potentially more than one node can receive the message. In [12], the network is large bounds are considered. In contrast, in a typical VANET topology ‘n’ does not increase asymptotically. In the gossip algorithms, at each time slot, each node can communicate at most one neighbor while a node can be contacted by multiple nodes. Our communication mechanism follows the opposite scenario: each node can potentially communicate with multiple nodes, but if a node is contacted by multiple nodes simultaneously, there will be a collision. In the PULL mechanism a node i, contacting node j leads to a transmission from node j to node i. If the entire node contacts node j, it broadcasts a message to all nodes, which can be cast as a broadcast transmission. However, in a single cell scenario, if more than two nodes are contacted, transmissions attack on the wireless channel while on the communication model in transmissions are successful. The information transmission considered in intends to deliver global information through local communication. However, in our problem, fast local information transmission is done through local communication and vehicles are not specifically interested in global information. More recently, in broadcast gossip algorithms are proposed for sensor networks to compute the average initial node calculation over the network. It is shown that the broadcast gossip almost surely converges to a consensus. In safety broadcasting, however, nodes are interested to receive the state information of all neighbor nodes not to achieve consensus over the network. III.

SAFETY MESSAGE RELIABILITY CONTROL

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pro-posed sub layer in Fig. 2. The message is produced based on the sensor output and according to the dictated format by SAE J2735 (Society of Automotive Engineers DSRC Message Set Dictionary standard). The header for the new sublayer is essentially the network coding overhead. Instead of passing the message directly to the WAVE stack, our sublayer combines the received messages, attaches the network coding overhead (sublayer header) and send it to the lower layer. The proposed reliability sub layer contains of two parts. The congestion control algorithm determines if a node should be active in a given CCH interval. If the node is not active in a CCH interval, the produced message will be dropped. If the node is active, it probabilistically transmits at each time slot during a CCH interval. We assume that the back off parameters of the IEEE 802.11p has been set to minimum and the physical carrier sensing is disabled. This can be done through the wireless card driver interface and ensures an instant transmission when a message is sent to the lower layer. The congestion control algorithm filters the produced messages in order to reduce the number of active nodes in each CCH interval. The Synchronized Persistent Coded Repetition (SPCR) algorithm defines the main functionality of the sub layer for transmission. At each time slot a random linear combination of all the queued messages can be transmitted by an active node. The following subsections detail the functionality and analysis of these components. First, we introduce the congestion control algorithm that limits the number of active nodes in a CCH interval. Then, the analysis for message retransmission is presented. Finally, message coding based on random linear network coding is utilized to further maximize the success probability. A. Congestion Control: When the number of vehicles in the cluster, N, is big the message reception probability drops considerably. We first derive the Ps (n) for IEEE 802.11p to see how it behaves by increasing the number of vehicles in a cluster. Theorem 1. The success probability for IEEE 802.11p broadcast node in a symmetric erasure channel with ‘n’ active nodes at the beginning of the CCH, and the contention window size, CW, can be written as:

Here X is the number of idle timeslots in a subframe in which ‘n’ packets has been successfully transmitted, and is given by:

Here TCCH is the CCH interval, This the PLCP interval,

This section demonstrates different components of the

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Proceedings of International Conference on Advancements in Engineering and Technology M is the Message size, R is the Channel rate, σ is the timeslot Interval, Tg is the Guard time, AIFS is the Arbitration interframe spacing, and pe is the Erasure probability. Proof: To find the success probability, we should find the Probability that all nodes pick distinct backoff counters (Ci ) and all transmissions are completed within the CCH period TCCH. Each successful transmission takes (Th+ MR +AIFS) seconds. So the maximum backoff counter must be less than The success probability can be written as follows: ∀ i, j: 1 ≤ i, j ≤ n and i _= j,

The first term is the complement of the Birthday Paradox Problem .when we have n people and min(X + 1, CW) days in a year and is equal to:

The second probability is that all Ci ’s are less than or equal to X. To see how the IEEE 802.11p broadcast mode performs when there is traffic congestion, we evaluated Ps(N) with the parameter in Table I, and for various erasure probabilities.The message size is assumed to be 200 bytes. Fig. 3 shows how the probability of success declines with increasing the number of nodes N. Even when there is no channel loss (pe = 0) the success probability degrades to less than 0.3 for 50 nodes. For higher erasure probabilities the congestion problem is more pronounced.

Fig. 3. Success probability vs. number of nodes: IEEE 802.11p broadcast mode.

Ideally, we are interested in delivering all ‘N’ messages with high probability, but for higher traffic collision, it is unattainable. The main solution to the congestion problem is message rate control. Rate control algorithm drops some of the

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messages to reduce congestion. This is the only way to manage excessive collisions and provide an overall acceptable reliability. Congestion control that’s depends on the system requirements and constraints and it can be implemented both in the application layer and in the MAC layer. Since the IEEE 802.11p is released and the network cards based on this standard is already in the market, solutions that are not based on MAC modifications are more attractive. Several proposed effective congestion control algorithms for VANETs are implemented in the application layer. Here, we contain a simple rate of that algorithm, which randomly filters the load. At the beginning of every frame each node randomly picks w sub frames and only transmits in those sub frames. Hence, the number of active nodes in a sub frame is a random number n ≤ N. Unlike the congestion control algorithm in which the rate is controlled based on the channel occupancy feedback, the feedback parameter in our method is the number of neighbors N, which is derived based on the most up-to-date neighborhood map. Since MTM is a random variable, we use E(MTM) for performance comparisons. The ‘w’ that maximizes the E(MTM) is set based on N. There are ways to choose w sub frames for each of N users. In order to have ‘ n’ active users in a sub frame, N − n users must choose w and the n active nodes must choose w−1 subframes out of the remaining Lf −1 subframes. Therefore, the expected value of MTM is:

By maximizing E (MTM), the optimal value for w can be found. A. Message Coding: In this section, we propose a novel algorithm that uses Random linear network coding in combination with message rebroadcasting. Based on the introduced repetition-based scheme in the earlier section, all nodes potentially have multiple transmission opportunities in a subframe. The same copy of the message is retransmitted to account for the channel loss. However, a node can linearly combine the already heard messages and transmit the coded message. In this section, we consider the application of random linear coding together with SPR. We call this algorithm SPCR (Synchronized Persistent Coded Repitition). The random linear coding algorithm is simple: each node enqueues all the received message and when it has a broadcasting opportunity based on its retransmission pattern, it broadcasts a random linear combination of all the already received message in its queue with the coefficients in GF(q) (Galois field with order q). At the end of the sub frame, if the node has n linearly independent coded vector it can decode all the original packets. Next, all nodes empty their queue and start a new transmission for the next time slot. To explain the overall structure of the reliability sub-layer, here we give a summary of how the different components

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Proceedings of International Conference on Advancements in Engineering and Technology work together. Each frame contains of Lf subframes (CCH intervals). The congestion control determines in which sub frames a node is active (w sub frames are select at random). In the active subframes, nodes start tansmissions a random linear combination of all the messages in their queues. Initially, each node only has its own message in the Queue. As times goes by and nodes overhear other broadcasting, their subsequent broadcasts is not only their messages, but a random linear combination of a subset that depending on their queue content. Algorithm 1 outlines the transmission algorithm of the sublayer. All nodes actively listen to the channel, when they are not transmitting, and queue all the received packets. The queue resets at the end of each CCH interval. IV.

NETWORK CODING ANALYSIS

Let us consider a single cell of n active node (u1, u2,· · · , un). The time is slotted and the nodes are synchronized. Each sub frame contain of L timeslots. At the beginning of each subframe each active node produces a message that should be received by all other nodes within the sub frame. The produced message is retransmitted several times during a sub frame. When a node has a transmission opportunity, it transmits a random linear combination of all already received packets in its queue. If mik represents the kth rebroadcasting of ui’s message, then the mik can be expressed as a linear combination of all the original messages: in which cj is a random coefficient in GF (q) and mj is the original produced message of node uj k . The coefficient vector c i = (c1, c2, · · · , cn) is a vector in n q . Note that some of ci’s can be zero. If a node receives n linearly independent equations, it can decode all the original messages. The coefficient vectors for the original messages at n the starting of a subframe are the standard basis for q . A. Coding Overhead: In random linear network coding, the random coefficients should be attached to the coded messages. In a congested network with large n the coding overhead can be comparable to the size of the message. For example, for GF (28), if there are 200 vehicles in a cluster, the maximum coding overhead will be 200 Bytes, which is comparable to the message size of 200-500 Bytes. To reduce the overhead, the authors have proposed to attach the seed of the random number generator. The seed specifies the sequence of random coefficients in a coded message. New coded messages can be produced from receiving coded messages. In this case, the seeds of all the included coded messages should be attached to the new coded message. This can potentially result in excessive overhead. As a result, the introduced algorithm can only encode the messages. However, in our proposed algorithm, we need to encode all the received coded messages. In the following, we show how we can indeed find the corresponding seed to the new coded message which considerably reduces the overhead. Linear Feedback Shift Registers (LFSRs) are an efficient

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way for implementing PRNGs (Pseudo Random Number Generators in a Gallois field). A LFSR implementation based on a primitive polynomial of GF (2m) has m states and has a period of 2m − 1. The state of the shift register represents the binary coefficients of the corresponding polynomial to a member of the Gallois field. Based on the starting seed (LFSR state), the sequence of the states of the LFSR is equivalent to the sequence of random numbers from a Galois field. The following lemma shows how the seed of the random coefficients of the random linear combination of coded messages relates to the seeds of the coded message coefficients V.

SIMULATION RESULT

In this section, we present realistic simulation results based on the introduced Nakagami channel model in the earlier section. The simulator is implemented using Mat lab based on the assumed channel and system model. Unlike the earlier sections, it is assumed that the erasure probability changes with distance. We assume 20 nodes are spaced horizontally with a spacing of 25m in a 500m road segment. Nodes are indexed from 1 to 20, in order, from left to right. A Nakagami channel model with the same parameter as previous section is utilized. All nodes broadcast with a channel rate of 12Mbps. The message size is 200 Bytes. The transmission power is assumed to be 20dBm for each node. The simulation results are averaged over 10000 runs. The loss probability (1 − Ps(n)) versus the node index can be seen in Fig. 4. It is observed that the SPCR loss probability of all nodes is almost the same. For SPR, the less probability is dependent on the location and is higher for all nodes. The location independent performance of SPCR is due to the cooperative nature of network coding. All nodes act as relays for their neighbors by including the messages of farther nodes in their coded packets. In SPR, even though message rebroadcasting can reduce the poor channel condition, since every node only repeats its own message, the edge nodes still are not able to receive all messages within a CCH interval. Although the derived loss probability upper bound in Theorem 2 is only valid for a symmetric erasure network, we have evaluated the bound for the maximum pe in the network as derived.

Fig. 4. Loss probability for all nodes: n = 20.

To further evaluate the performance under a more realistic network model, SPCR and SPR have been implemented in the ns-2 simulator. Unlike the assumed channel model for our analysis in ns-2 some of the collisions can be resolved due to capture. The transmission power for every node is set to

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Proceedings of International Conference on Advancements in Engineering and Technology 760mw (Class D in the IEEE 802.11p standard) and the transmitter and receiver antenna gain is 2. The message size is 200 Bytes. The radio frequency, reception and carrier threshold have been set according to the IEEE 802.11p standard. A 4-lane road segment of length 500m and 1km is assumed. In each lane a vehicle is placed uniformly every d meters. Four traffic densities of 10, 15, 20 and 25 nodes per lane are assumed. All nodes are assumed to be active. The lower node densities correspond to highways in which the vehicle interspacing is larger. Higher traffic densities represent the urban areas. The simulations are performed for 100s. The average loss probability over all nodes and within the simulation time is calculated. The simulation results for channel rates of 12Mbps and 27Mbps (maximum rate of IEEE 802.11p) and for the 500m road segment topology can be seen in Fig. 13. It is observed that SPCR can significantly benefit from the rate increase. For example, for n = 100, in SPCR, by increasing the rate from 12Mbps to 27Mbps the average loss probability drops one order of magnitude in less than 0.05, while for SPR the average loss probability remains at 1. This proves the significant gain that can be achieved through network coding specially in dense topologies. As we mentioned in the earlier section, increasing the rate increases the number of time slots in a sub-frame which provides more opportunities for broadcasting the coded messages. Unlike the SPR in which the additional transmission chance are not necessarily helpful for all the receivers, in SPCR, most of the receivers can advantage from the received coded message by expanding their subspace of receiving coded vectors. The simulation results for the 1km road segment topology can be observed in Fig.5. Due to longer transmission ranges, channel quality is worse compared to the earlier topology. It can be seen that SPCR performance is robust.

Fig. 5. Expected loss probability vs. number of nodes.

It can be seen that SPCR performance is robust. To channel error and does not change significantly compared to the earlier topology. However, the SPR performance suffers from lower channel quality. For example, for 40 nodes and 27Mbps rate, the average loss probability increases to more than 0.56 from 0.08. This shows that network coding not only is effective in dense topologies, but also is robust to channel errors.

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Fig. 6. Expected loss probability vs. number of nodes

VI.

CONCLUSION

We have proposed a sublayer that optimizes the reliability of periodic broadcasting in VANETs. The core of our design is the random linear network coding which is used to provide reliability for small safety messages with low overhead. We have also studied how the message rebroadcasting can be used when there is congestion. Numerical results based on our analysis confirm the superior performance for our method compared to earlier schemes. Our design can be implemented in conjunction with the WAVE architecture and does not need any modification to the WAVE communication stack. VII.

REFERENCE

[1] B. Xu, A. Ouksel, and O. Wolfson, “Opportunistic resource exchange in inter-vehicle ad-hoc networks,” in Proc. 2004 IEEE International Conf. on Mobile Data Management, pp. 4–12. [2] “IEEE Standard for Wireless Access in Vehicular Environments (WAVE)– Multi-channel Operation,” pp. 1–89, 2011, IEEE Std 1609.4-2010 (Revision of IEEE Std 1609.4-2006). [3] Y. P. Fallah, C. Huang, R. Sengupta, and H. Krishnan, “Congestion control based on channel occupancy in vehicular broadcast networks,” in Proc. 2010 IEEE Veh. Technol. Conf. – Fall. [4] Y. Fallah, C.-L. Huang, R. Sengupta, and H. Krishnan, “Analysis of information dissemination in vehicular ad-hoc networks with application to cooperative vehicle safety systems,” IEEE Trans. Veh. Technol., vol. 60, no. 1, pp. 233–247, Jan. 2011. [5] Q. Xu, T. Mak, J. Ko, and R. Sengupta, “Vehicle-to-vehicle safety messaging in DSRC,” in Proc. 2004 ACM International Workshop Veh. Ad Hoc Netw., pp. 19–28. [6] B. Hassanabadi and S. Valaee, “Reliable network coded MAC in vehicular ad-hoc networks,” in Proc. 2010 IEEE Veh. Technol. Conf. [7] Q. Xu, T. Mak, J. Ko, and R. Sengupta, “Medium access control protocol design for vehicle-to-vehicle safety messages,” IEEE Trans. Veh. Technol., vol. 56, no. 2, pp. 499–518, Mar. 2007. [8] F. Farnoud, B. Hassanabadi, and S. Valaee, “Message broadcast using optical orthogonal codes in vehicular communication systems,” 2007 ICST QSHINE Workshop on Wireless Netw. Intelligent Transportation Syst. [9] D. S. Lun, M. Medard, R. Koetter, and M. Effros, “On coding for reliable communication over packet networks,”Physical Commun., vol. 1, no. 1, pp. 3–20, [10] J.-S. Park, U. Lee, S.-Y. Oh, M. Gerla, D. S. Lun, W. W. Ro, and J. Park, “Delay analysis of car-to-car reliable data delivery strategies based on data mulling with network coding,” IEICE Trans., vol. 91-D, no. 10, pp. 2524– 2527, 2008. [11] Z. Yang, M. Li, and W. Lou, “CodePlay: live multimedia streaming in VANETs using symbol-level network coding,” in Proc. 2010 IEEE Int. Netw. Protocols Conf., pp. 223–232, [12] F. Ye, S. Roy, and H. Wang, “Efficient inter-vehicle data dissemination,” in Proc. 2011 IEEE Veh. Technol. Conf. – Fall, pp. . 1–5

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An Efficient and Accurate Misbehavior Detection Scheme in Adversary Environment Kanagarohini.V1, Ramya.K2 1

Student:Sree Sowdambika College of Engineering Guide:Sree Sowdambika College of Engineering

1 2

rohini.cse01@gmail.com sri.ramya531@gmail.com

Abstract— Misbehaviour detection is regarded as a variation in network conditions, difficult to predict mobility great challenge in the adversary environment because of distinct network characteristics. Harmful and egocentric behaviours illustrate an insecure threat against routing in delay tolerant networks (DTNs). In order to address this, in this paper, we propose iTrust, a probabilistic misbehaviour detection scheme for efficient and accurate misbehaviour detection in DTNs. Our iTrust scheme introduces the periodically available Trusted Authority (TA) to estimate the node’s behavior based on the collected routing evidences. To further enhance the power of the proposed model, we associate the detection probability with node’s reputation for effective inspection. Keywords—Delay Tolerant Networks, Trusted Authority, Reputation.

I. INTRODUCTION

II. RELATED WORK

Delay Tolerant Network is a communication network designed to tolerate long delays and outages. The current networking technology depends on a set of basic assumptions that are not true in all environments. The first and most important assumption is that an end-to-end connection exists from the source to the destination. This assumption can be easily contravened due to mobility, power saving etc. Examples of such networks are sensor networks with scheduled infrequent connectivity, vehicular DTNs that publish local ads, traffic reports, parking information [1]. Delay tolerant network (DTN) is an attempt to extend the reach of networks. It give an assurance to enable communication between “challenged” networks.

Fig. 1, Delay Tolerant Networking Environment Delay Tolerant Networks have unique characteristics like lack of contemporaneous path, short range contact high

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patterns and long feedback delay. Because of these unique characteristics the Delay Tolerant Networks (DTNs) move to an approach known as “store-carry-and-forward” strategy where the bundles can be sent over the existing link and buffered at the next hop until the next link in the path appears and the routing is determined in an “opportunistic” fashion. In DTNs a node could misbehave by refusing to forward the packets, dropping the packets even when it has the potential to forward (e.g., sufficient memory and meeting opportunities) or modifying the packets to launch attacks. These types of malicious behaviors are caused by rational or malicious nodes, which try to maximize their own benefits. Such malicious activities pose a serious threat against network performance and routing. Hence a trust model is highly enviable for misbehavior detection and attack mitigation.

Routing misbehavior detection and mitigation has been well crammed in traditional mobile ad hoc networks. These methodologies use neighborhood monitoring or destination acknowledgement (ACK) to detect dropping of packets [2]. In the mobile ad hoc networks (MANET) first complete route is established from source to destination, before transmitting the packet. But in DTN the nodes are intermittently connected, hence there is no possibility for route discover and it has other unique characteristics like dynamic topology, short range contact, long feedback delay which made the neighborhood monitoring unsuitable for DTN. Although many routing algorithms [3, 4, 5, 6, 7] have been proposed for DTNs, most of them do not consider the node’s willingness to forward the packet and implicitly assume that a node is willing to forward packets for all others. They may not work well since some packets are forwarded to nodes unwilling to relay, and will be dropped. There are quite a few proposals for misbehaviour detection which are based on forward history verification (e.g., multi layer formation [8]) and by providing encounter tickets [9], which incur high transmission overhead as well as high verification cost. Different from the exiting works in which the Trusted Authority (TA) performs the auditing based on checking the contact history [10], is critical and time consuming. Our proposed system uses nectar protocol for selecting the appropriate intermediate node such that the

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Proceedings of International Conference on Advancements in Engineering and Technology inspection or auditing process can be simplified and the packet dropping rate can be considerably reduced. To achieve a tradeoff between detection cost and security, our Trust model relies on inspection game [11] based on game theory. This introduces a periodically available Trusted Authority (TA) to judge the nodes based on collected routing evidences. Our Trust model jointly considers the incentive and malicious node detection scheme in the single framework along with the effective nectar protocol for selecting the appropriate intermediate node. The contributions of this paper can be summarized as follows. 1. We propose a general misbehavior detection framework based on a series of newly introduced data forwarding evidences. The proposed evidence framework could not only detect various misbehaviors but also be compatible to various routing protocols. 2. Malicious node detection is carried out by the Trusted Authority (TA) based on the evidences generated by nodes, which are selected by the application of protocol. 3. Hence packet dropping rate can be considerably reduced and the performance of the network can be improved.

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applied to delegation-based routing protocols or multicopybased routing ones, such as MaxProp [18] and ProPHET [19]. We assume that the network is loosely synchronized (i.e., any two nodes should be in the same time slot at any time).

III. PRELIMINARY A. System Model Delay Tolerant Network consist of mobile devices owned by individual users. Each node i is assumed to have a unique ID Ni and a corresponding public/private key pair. We assume that each node must pay a deposit before it joins the network, and the deposit will be paid back after the node leaves if there is no misbehavior activity of the node. we assume that a periodically available TA exists so that it could take the responsibility of misbehavior detection in DTN. For a specific detection target Ni, TA will request Ni’s forwarding history in the global network. Therefore, each node will submit its collected Ni’s forwarding history to TA via two possible approaches. In a pure peer-to-peer DTN, the forwarding history could be sent to some special network components (e.g., roadside unit (RSU) in vehicular DTNs or judge nodes in [10]) via DTN transmission. In some hybrid DTN network environment, the transmission between TA and each node could be also performed in a direct transmission manner (e.g., WIMAX or cellular networks [14]). We argue that because the misbehavior detection is performed Periodically, the message transmission could be performed in a batch model, which could further reduce the transmission overhead. B. Routing Model We adopt the single-copy routing mechanism such as First Contact routing protocol, and we assume the communication range of a mobile node is finite. Thus, a data sender out of destination node’s communication range can only transmit packetized data via a sequence of intermediate nodes in a multihop manner. Our misbehaving detection scheme can be

ISBN NO : 978 - 1502893314

Fig 2: Trust model architecture HOTE – Hand Over Task Evidence FD – Forwarding FC – Forward Chronicle CL- Contact Log NI - Neighborhood Index Ni, Nj, Nk – Intermediate Nodes CC – Contact Counter TOC- time of contact C. Adversary Model First of all, we assume that each node in the networks is rational and a rational node’s goal is to maximize its own profit. In this work, we mainly consider two kinds of DTN nodes: selfish nodes and malicious nodes. Due to the selfish nature and energy consuming, selfish nodes are not willing to forward bundles for others without sufficient reward. As an adversary, the malicious nodes arbitrarily drop others’ bundles (black hole or gray hole attack), which often take place beyond others’ observation in a sparse DTN, leading to serious performance degradation. Note that any of the selfish actions above can be further complicated by the collusion of two or more nodes.

IV. ROUTING TESTIMONY GENERATION PHASE The basic iTrust has two phases, including routing testimony generation phase and auditing phase. In the evidence generation phase, the nodes will generate contact and data forwarding evidence for each contact or data forwarding. In the subsequent auditing phase, TA will

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distinguish the normal nodes from the misbehaving nodes. For an example, we take a three-step data forwarding process. consider node X has packets, which will be delivered to node Z. If node X meets another node Y that could helps to forward the packets to Z, X will replicate and forward the packets to Y. Afterwards, Y will forward the packets to Z when Z arrives at the transmission range of Y. In this process, we define three kinds of data forwarding evidences that could be used to judge if a node is a malicious one or not:

accordingly. Each node also maintains a contact counter, which keeps track of how often the nodes meet each other. When two nodes Nj and Nk meet, a new contact log Ej<->kcontact will be generated. Suppose that Mj<->k = {Nj ,Nk, Tts}. Nj and Nk will generate their signatures Sigj = SIGj {H (Mj->k)} and Sigk = SIGk{H(Mj<->k)}. Therefore, the contact history evidence could be obtained as follows:

A. Hand Over Task Evidence

The contact log will be stored at both of meeting nodes. In the audit phase both the nodes will submit their logs to the TA. Maintenance of contact history could prevent the black hole or grey hole attack. The nodes chosen by the nectar protocol with sufficient contact with other users, but if it fails to forward the data, will be regarded as a malicious or selfish one.

Hand Over Task evidences are used to record the number of routing tasks assigned from the upstream nodes to the target node Nj. We assume that source node (Nsrc) has message M, in order to forward to the destination (Ndst). For simplicity of presentation, consider that message is stored at the intermediate node (Ni), when Nj comes within the transmission or radio range of Ni ,then it will determine by means of nectar protocol whether to choose node j(Nj) as the intermediate node or not, in order to forward message M to the destination. If node j (Nj) is the chosen next node then the flag bit will be enabled (or flag = 1) and the Task evidence Eiâ&#x2020;&#x2019;jtask need to be generated, to demonstrate that a new task has been assigned from node i (Ni) to node j (Nj). Where Tts and TExp refer to the time stamp and the expiration time of the packets. we set Mi>jM={M,Nsrc, flag, Ni, Nj,Ndst, Tts, TExp, Sigsrc}, where Sigsrc= Sigsrc(H( M,Nsrc, Ndst, TExp)) refers to the signature generated by the source nodes on message M. Node Ni generates the signature Sigi =SIGi{ Mi->jM } to indicate that this forwarding task has been delegated to node Nj while node Nj generates the signature Sigj =SIGj{ IMi->jM } to show that Nj has accepted this task. Therefore, we obtain the delegation task evidence as follows:

Ej<->k contact = {Mj<->k, Sigj, Sigk} (3)

V. AUDITING PHASE Since the selection of intermediate node is based on the Nectar protocol, the dropping rate of packect is reduced considerably. In order to further improve the network performance and to avoid packet dropping, our trust model introduces the Trusted Authority (TA), which periodically launches the investigation request. In the auditing phase, the Trusted Authority (TA) will send the investigation request to node Nj in a global network during a certain period [t1, t2]. Then, given N as the set of nodes in the network, each node in the DTN will submit itâ&#x20AC;&#x2122;s collected {Ei->jtask, Ej->kforward, Ej<->kcontact} to TA. After collecting all of the evidences related to Nj , TA obtains the set of task evidence Stask, the set of messages forwarded Sforward and the set of contacted nodes Scontact. To check if a suspected node Nj is malicious or not, TA should check if any message forwarding request has been honestly fulfilled by Nj.

Eiď&#x192; jtask = {Mi->jM , Sigi, Sigj} (1)

A. Reliable data forwarding with adequate users

B. Forwarding Chronicle evidence When Nj meets the next intermediate node Nk, Nj will check if Nk is the desirable next intermediate node in terms of a specific routing protocol. If yes Nj will forward the packets to Nk, who will generate a forwarding history evidence to demonstrate that Nj has successfully finished the forwarding task. Nk will generate a signature Sigk=SIGk{H(Mj->kM)} to demonstrate the authenticity of forwarding history evidence. Therefore, the complete forwarding history evidence is generated by Nk as follows: Ej->kforward = {Mj->kM, Sigk} (2) In the audit phase, the node which is inspected will submit its forwarding history evidence to TA to demonstrate that it has tried its best to accomplish the routing tasks, which are defined by hand over task evidences.

C. Contact log evidence Whenever two nodes meet, a new contact log is generated and the neighbourhood index is updated

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A normal user will honestly follow the routing protocol by forwarding the messages to the sufficient users. Therefore, the given message m is in Stask, the data is forwarded to the presence of adequate users. The requested message has been forwarded to the next hop, the chosen next hop nodes are desirable nodes according to a specific DTN routing protocol, and the number of forwarding copies satisfy the requirement defined by a multicopy forwarding routing protocol.

B. Reliable data forwarding with inadequate users A normal users will also honestly perform the routing protocol but fail to achieve the desirable results due to lack of adequate users. Therefore, given the message m is in Stask, the data is forwarded to the presence of adequate users. There are two cases are here. First case is that there is no contact during period [Tts (m), t2]. The second case is that only a limited number of contacts are available in this period and the number of contacts is less than the number of copies required

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Proceedings of International Conference on Advancements in Engineering and Technology by the routing protocols. In both cases, even though the DTN node honestly performs the routing protocol, it cannot fulfill the routing task due to lack of sufficient contact chances. We still consider this kind of users as honest users.

C. A misbehaving data forwarding with/without adequate users A misbehaving node will drop then packets or refuse to forward the data even when there are sufficient contacts. There are three cases are here. The first case is the forwarder refuses to forward the data even when the forwarding opportunity is available. The second case is that the forwarder has forwarded the data but failed to follow the routing protocol. The last case is that the forwarder agrees to forward the data but fails to propagate the enough number of copies predefined by a multicopy routing protocol

VI. ALGORITHM FOR DETECTION

MISBEHAVIOR

The TA judges if node Nj (Suspected node) is malicious or not by triggering the Malicious node detection algorithm. Where node j is the suspected malicious node, Stask is the set of hand over task evidence, Sforward is the set of forward chronicle, and R is the set of contacted nodes, Nk(m) as the set of next-hop nodes chosen for message forwarding, C represents the punishment (lose of deposit), we denotes the compensation (virtual currency or credit) paid by TA.

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In this algorithm, we introduce Basic Detection, which takes j, Stask, Sforward, [t1, t2], R, D as well as the routing requirements of a specific routing protocol R, D as the input, and output the detection result “1” to indicate that the target node is a misbehavior or “0” to indicate that it is an honest node. To prevent malicious users from providing fake delegation/forwarding/contact evidences, TA should check the authenticity of each evidence by verifying the corresponding signatures, which introduce a high transmission and signature verification overhead. Algorithm 2. The Proposed Malicious Node Detection algorithm 1.

initialize the number of nodes n

for i1 to n do

3. 4.

generate a random number mi from 0 to 10n _ 1 if mi/10n < pb then

ask all the nodes (including node i) to provide evidence about node i

if Basic Detection(I,Stask,Sforward,[t1, t2],R,D) then

give a punishment C to node i

Else

pay node i the compensation w

Algorithm 1. The basic misbehavior detection algorithm 1.

procedure BASICDETECTION ((j,Stask, Sforward, [t1, t2], R)) for each m is in Stask do

10. end if

if m is not in Sforward and R≠0 then

3. 4.

11. Else

return 1

12. pay node i the compensation w

else if m is in Sforward and Nk(m) is not in R

13. end if

then 6. 7.

8. 9.

14. end for

return 1 else if m is in Sforward and Nk(m) is in R then |Nk(m)| is less than D then return 1

The above algorithm shows the details of the proposed probabilistic misbehavior detection scheme. For a particular node i, TA will launch an investigation at the probability of pb. If i could pass the investigation by providing the corresponding evidences, TA will pay node i a compensation w; otherwise, i will receive a punishment (lose its deposit).

end if

10.

end for

11.

return 0

12. end procedure

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VII.

PROBABILITY FIXING INSPIRED BY GAME THEORY

There are two strategies available for the trusted authority and the nodes. The Trusted Authority can choose inspecting (I) or not inspecting (N). Each node also has two strategies, forwarding(F) and offending (O).

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Proceedings of International Conference on Advancements in Engineering and Technology Theorem: If TA inspects at the probability of Pb = g+£/w+C in Trust Model, a rational node must choose forwarding strategy, and the TA will get a higher profit than it checks all the nodes in the same round. Proof: This is a static game of complete information, though no dominating strategy exists in this game, there is a mixed Nash Equilibrium point. If the node chooses offending strategy, its payoff is

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take all the nodes whose PLR larger than 0 as the malicious ones. On the other hand, since a normal node may also be identified as the malicious one due to the depletion of its buffer, we need to measure the false alert of iTrust and show that iTrust has little impact on the normal users who adhere to the security protocols. Thus, we use the misidentified rate to measure the false negative rate. Moreover, we evaluate the transmission overhead Costtransmission and verification overhead Costverification in terms of the number of evidence transmission and verification for misbehavior detection. In the next section, we will evaluate the effectiveness of iTrust under different parameter settings.

πw(S) = −C · (g + £/w + C) + w · (g + £/w + C)= w − g –£ If the node chooses forwarding strategy, its payoff is πw (W) = Pb · (w − g) + (1 − Pb) · (w − g) = w – g The latter one is obviously larger than the previous one. Therefore, if TA chooses the checking probability g+_/w+C, a rational node must choose the forwarding strategy. Furthermore, if TA announces it will inspect at the probability Pb = g+£/w+C to every node, then its profit will be higher than it checks all the nodes, for v − w − (g + £ /w + C) · h > v− w– h Here the latter part in the inequality is the profit of TA when it checks all the nodes. Note that the probability that a malicious node cannot be detected after k rounds is (1− g+£ /w+C )k  0, if k∞. Thus it is almost impossible that a malicious node cannot be detected after a certain number of rounds.

VIII. EXPERIMENT RESULTS We set up the experiment environment with the opportunistic networking environment (NS2) simulator, which is designed for evaluating DTN routing and application protocols. In our experiment, we adopt the First Contact routing protocol, which is a single-copy routing mechanism. We set the time interval T to be about 3 hours as the default value, and we deploy 50, 80, 100 nodes on the map, respectively. With each parameter setting, we conduct the experiment for 100 rounds. We use the packet loss rate (PLR) to indicate the misbehavior level of a malicious node. In DTNs, when a node’s buffer is full, a new received bundle will be dropped by the node, and PLR denotes the rate between the dropped bundles out of the received bundles. But, a malicious node could pretend no available buffer and, thus, drop the bundles received. Thus, PLR actually represents the misbehavior level of a node. For example, if a node’s PLR is 1, it is totally a malicious node who launches a black hole attack. If a node’s PLR is 0, we take it as a normal node. Further, if 0 < PLR < 1, the node could launch a gray hole attack by selectively dropping the packets. In our experiment, we use the detected rate of the malicious nodes to measure the effectiveness of iTrust, and we

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A. The Impact of Percentage of Malicious Nodes on iTrust We use malicious node rate (MNR) to denote the percentage of the malicious nodes of all the nodes. In this experiment, we consider the scenarios of varying MNR from 10 to 50 percent. In this experiment, PLR is set to be 1, and the velocity of 80 nodes varies from 10:5 to 11:5 m=s. The message generation time interval varies from 25 to 35 s, and the TTL of each message is 300 s. The experiment result is shown in Fig. 3. Fig. 3a shows that three curves have the similar trends, which indicate that iTrust could achieve a stable performance with different MNRs. Even though the performance of iTrust under high MNR is lower than that with low MNR, the detected rate is still higher than 70 percent. Furthermore, the performance of iTrust will not increase a lot when the detection probability exceeds 20 percent, but it is good enough when the detection probability is more than 10 percent. Thus, the malicious node rate has little effect on the detected rate of malicious nodes. That means iTrust will be effective, no matter how many malicious nodes there are. Further, a high malicious node rate will help reduce the misidentified rate as shown in Fig. 3b because the increase of the malicious nodes will reduce the proportion of the normal nodes who will be misidentified.

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Fig. 4. Experiment results with user number of 100, 80, 50.

Fig. 3. Experiment results with different MNRs. B. The Evaluation of the Scalability of iTrust First, we evaluate the scalability of iTrust, which is shown in Fig. 4. As we predict in (12), the number of nodes will affect the number of generated contact histories in a particular time interval. So we just measure the detected rate (or successful rate) and misidentified rate (or false positive rate) in Fig. 4. Fig. 4a shows that when detection probability p is larger than 40 percent, iTrust could detect all the malicious nodes, where the successful detection rate of malicious nodes is pretty high. It implies that iTrust could assure the security of the DTN in our experiment. Furthermore, the misidentified rate of normal users is lower than 10 percent when user number is large enough, as shown in Fig. 4b, which means that iTrust has little impact on the performance of DTN users. Therefore, iTrust achieves a good scalability.

C. The Impact of Various Packet Loss Rate on ITrust In the previous section, we have shown that iTrust could also thwart the gray hole attack. In this section, we evaluate the performance of iTrust with different PLRs. In this experiment, we measure the scenarios of varying PLR from 100 to 80 percent. We set MNR as 10 percent, and the speed of 80 nodes varying from 10:5 to 11:5 m=s. The message generation interval varies from 25 to 35 s, and the TTL of each message is 300 s. The experiment result and PLRs have little effect on the performance of iTrust, as shown in Fig. 5. This implies iTrust will be effective for both black hole attack and gray hole attack. The misidentified rate is not affected by PLRs either. It is under 8 percent when the detection probability is under 10 percent. Thus, the variation of PLR will not affect the performance of iTrust.

Fig. 5. Experiment results with different PLRs.

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IX. CONCLUSION In this paper we propose a Trust Model which could effectively detect the malicious node and ensures secure transmission of data. The selection of neighbour node is based on AODV protocol, by which the packet dropping rate is considerably reduced and it also simplifies the work of Trusted Authority (TA). We also reduce the detection overhead by introducing the Trusted Authority (TA) designed on the basis of inspection theory, in a periodic fashion. REFERENCES 1] R. Lu, X. Lin, H. Zhu, and X. Shen, “SPARK: A New VANETBased Smart Parking Scheme for Large Parking Lots,” Proc. IEEE INFOCOM ’09, Apr. 2009. [2] T. Hossmann, T. Spyropoulos, and F. Legendre, “Know the Neighbor: Towards Optimal Mapping of Contacts to Social Graphs for DTN Routing,” Proc. IEEE INFOCOM ’10, 2010. [3] Q. Li, S. Zhu, and G. Cao, “Routing in Socially Selfish Delay-Tolerant Networks,” Proc. IEEE INFOCOM ’10, 2010. [4] H. Zhu, X. Lin, R. Lu, Y. Fan, and X. Shen, “SMART: A Secure Multilayer Credit-Based Incentive Scheme for DelayTolerant Networks,” IEEE Trans. Vehicular Technology, vol. 58, no. 8, pp. 828-836, 2009. [5] H. Zhu, X. Lin, R. Lu, P.-H. Ho, and X. Shen, “SLAB: Secure Localized Authentication and Billing Scheme for Wireless Mesh Networks,” IEEE Trans. Wireless Comm., vol. 17, no. 10, pp. 3858- 3868, Oct. 2008. [6] Q. Li and G. Cao, “Mitigating Routing Misbehavior in Disruption Tolerant Networks,” IEEE Trans. Information Forensics and Security, vol. 7, no. 2, pp. 664-675, Apr. 2012. [7] S. Marti, T.J. Giuli, K. Lai, and M. Baker, “Mitigating Routing Misbehavior in Mobile Ad Hoc Networks,” Proc. ACM MobiCom ’00, 2000. [8] R. Lu, X. Lin, H. Zhu, and X. Shen, “Pi: A Practical Incentive Protocol for Delay Tolerant Networks,” IEEE Trans. Wireless Comm., vol. 9, no. 4, pp. 1483-1493, Apr. 2010. [9] F. Li, A. Srinivasan, and J. Wu, “Thwarting Blackhole Attacks in Disruption-Tolerant Networks Using Encounter Tickets,” Proc. IEEE INFOCOM ’09, 2009. [10] E. Ayday, H. Lee, and F. Fekri, “Trust Management and Adversary Detection for Delay-Tolerant Networks,” Proc. Military Comm. Conf. (Milcom ’10), 2010. [11] D. Fudenberg and J. Tirole, Game Theory. MIT Press, 1991. [12] M. Rayay, M.H. Manshaeiy, M. Flegyhziz, and J. Hubauxy, “Revocation Games in Ephemeral Networks,” Proc. 15th ACM Conf. Computer and Comm. Security (CCS ’08), 2008. [13] S. Reidt, M. Srivatsa, and S. Balfe, “The Fable of the Bees: Incentivizing Robust Revocation Decision Making in Ad Hoc Networks,” Proc. 16th ACM Conf. Computer and Comm. Security (CCS ’09), 2009. [14] B.B. Chen and M.C. Chan, “Mobicent: A Credit-Based Incentive System for Disruption-Tolerant Network,” Proc. IEEE INFOCOM ’10, 2010.

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[15] S. Zhong, J. Chen, and Y.R. Yang, “Sprite: A Simple Cheat-Proof, Credit-Based System for Mobile Ad-Hoc Networks,” Proc. IEEE INFOCOM ’03, 2003. [16] J. Douceur, “The Sybil Attack,” Proc. Revised Papers from the First Int’l Workshop Peer-to-Peer Systems (IPTPS ’01), 2001. [17] R. Pradiptyo, “Does Punishment Matter? A Refinement of the Inspection Game,” Rev. Law and Economics, vol. 3, no. 2, pp. 197- 219, 2007. [18] J. Burgess, B. Gallagher, D. Jensen, and B. Levine, “Maxprop: Routing for Vehicle-Based Disruption-Tolerant Networks,” Proc. IEEE INFOCOM ’06, 2006. [19] A. Lindgren and A. Doria, “Probabilistic Routing Protocol for Intermittently Connected Networks,” draftlindgren-dtnrg-prophet- 03, 2007. [20] W. Gao and G. Cao, “User-Centric Data Dissemination in Disruption-Tolerant Networks,” Proc. IEEE INFOCOM ’11, 2011. [21] A. Keranen, J. Ott, and T. Karkkainen, “The ONE Simulator for DTN Protocol Evaluation,” Proc. Second Int’l Conf. Simulation Tools and Techniques (SIMUTools ’

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A FRAMEWORK FOR SECURE DATA TRANSMISSION IN DEFENSE NETWORK Dhivya.G1, Rajeswari.G2 1

Student: Sree Sowdambika College Of Engineering, Anna University Guide: Sree Sowdambika College Of Engineering, Anna University 1 divya.jillu3@gmail.com 2 prajasri10@gmail.com until the connection would be eventually established.DTN ABSTRACT— In many defense network, introduced supply nodes where data are stored or connections of wireless devices carried by soldiers may replicated such that only authorized mobile nodes can be temporarily disconnected by jamming, access the necessary information quickly and efficiently. environmental factors, and mobility, especially when Many military applications require increased protection of they operate in hostile environments. Disruptionconfidential data including access control methods that tolerant network (DTN) technologies are becoming are cryptographically enforced. In many cases, it is successful solutions that allow nodes to communicate desirable to provide differentiated access services such with each other in these extreme networking that data access policies are defined over exploiter environments.DTN networks introduced supply nodes attributes or roles, which are managed by the key sway. where data are stored or replicated such that only For example, in a disruption-tolerant military network, a authorized mobile nodes can access the necessary commander may store confidential information at a information quickly and efficiently. In this proposed supply node, which should be entered by the subscriber of system, cipher-text policy attribute based encryption “Corps 1” who is participating in “Region 2.” In this case, (CP-ABE) provides a scalable method of cipher data, it is a reasonable assumption that multiple key sway are such that the encryptor defines the attributes set that likely to manage their own dynamic attributes for soldiers the decryptor needs to possess in order to decrypt the in their deployed regions or echelons, which could be encoded text. This paper provides how the data are frequently changed (e.g., the attribute representing the transmitted in a very safety manner. current location of moving soldiers). We refer to this Keywords— wireless devices, communication, DTN architecture where multiple sway issue and manage authorized mobile nodes, attribute set their own attribute keys independently as a decentralized DTN.[10] I. INTRODUCTION Attribute based encryption [11]-[14] is a vision A disruption-tolerant network (DTN) is a of public key encryption that allows exploiters to encrypt network designed so that temporary or intermittent and decrypt messages based on exploiter attributes (e.g., transmission troubles, flaws and abnormalities have the the attribute representing the current location of moving least possible opposite crash. There are various features to soldiers)[4],[8],[9]. In a typical execution, the length of the strong scheme of a DTN, incorporating: 1. The use of the encrypted text is proportional to the number of fault-tolerant methods and technologies. 2. The quality of attributes associated with it and the decryption time is graceful degradation under adverse conditions or extreme proportional to the number of attributes used during traffic loads. 3. The ability to prevent or quickly recover decryption. from electronic attacks. 4. Ability to function with However, the problem of applying the ABE to minimal latency even when routes are ill-defined or DTNs introduces several security and secrecy challenges. unreliable. Since some exploiters may change their associated Mobile nodes in defense environs, such as a attributes at some point (for example, motion in their combat zone or a vicious area are likely to suffer from area), or some unique keys might be compromised, key intermittent network connectivity and frequent partitions. revocation (or update) for each attribute is necessary in Disruption-tolerant network (DTN) technologies are order to make systems secure. However, this issue is even becoming successful solutions that allow wireless devices additional inconvenient, especially in ABE systems, since carried by soldiers to communicate with each other and each trait is conceivably shared by multiple exploiters access the confidential information or command reliably (henceforth, we refer to such a collection of exploiters as by exploiting external supply nodes. Typically, when a trait group). This points that revocation of any attributes there is no end-to-end connection between a source and a or any single exploiter in a trait group would affect the target pair, the data from the origin node may need to wait other exploiters in the group. For example, if an exploiter in the intermediate nodes for a substantial amount of time 2

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joins or leaves a trait group, the associated attribute key should be changed and redistributed to all the other members in the same group for backward or forward secrecy. It may result in neck of a bottle during rekeying procedure or safety ignominy due to the windows of vulnerability if the previous attribute key is not updated immediately. Another challenge is the key escrow problem. In CP-ABE, the key authorization generates private keys of exploiters by applying the sway’s master secret keys to exploiters’ associated set of traits. The last challenge is the coordination of attributes issued by different sway. For example, suppose that traits “role 1” and “region 1” are managed by the sway A, and “role 2” and “region 2” are managed by the sway B. Then, it is impossible to generate an access policy ((“role 1” OR “role 2”) AND (“region 1” or “region 2”)) in the previous schemes because the OR logic between attributes issued by different sway cannot be implemented. This is due to the fact that the different sway generate their own attribute keys using their own independent and individual master secret keys.

II. DISRUPTION TOLERENT NETWORK Military applications in the DTN arena are substantial, allowing the retrieval of critical information in mobile battlefield scenarios using only intermittently connected network communications. For these types of applications, the delay tolerant protocol should transmit data segments across multiple-hop networks that consist of differing regional networks based on environmental network parameters (latency, loss, BER). This essentially implies that data from low-latency networks for which TCP may be suitable must also be forward across the long-haul interplanetary link. DTN achieves message reliability via employing custody transfer. The concept of custody transfer, where responsibility of some data segment (bundle or bundle fragment), migrates with the data segment as it progresses across a series of network hops is a fundamental strategy such that reliable delivery is accomplished on a hop-by-hop basis instead of an endto-end basis DTN is a set of protocols that act together to enable a standardized method of performing store and forward communications.DTN operates in two basic environments: low-propagation delay and highpropagation delay. In a low-propagation environment such as may occur in near-planetary or planetary surface environments, DTN bundle agents can utilize underlying Internet protocols that negotiate connectivity in real-time. In high-propagation delay environments such as deep space, DTN bundle agents must use other methods, such as some form of scheduling, to enable connectivity between the two agents. The convergence layer protocols provide the standard methods for transferring the bundles

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over various communications paths. The bundle agent discovery protocols are the equivalent to dynamic routing protocols in IP networks. To date, the location of bundle agents, DTN agents, has been managed, analogous to static routing in internet protocol (IP) networks. The security protocols for DTN are important for the bundle protocol. The stressed environment of the underlying networks over which the bundle protocol will operate makes it important that the DTN be protected from unauthorized use, and this stressed environment poses unique challenges on the mechanisms needed to secure the bundle protocol. DTNs are likely to be deployed in organizationally heterogeneous environments where one does not control the entire network infrastructure. Furthermore, DTNs may very likely be deployed in environments where a portion of the network might become compromised, posing the usual security challenges related to confidentiality, integrity and availability. Fault-tolerant systems are designed so that if a component fails or a network route becomes unusable, a backup component, procedure or route can immediately take its place without loss of service. At the software level, an interface allows the administrator to continuously monitor network traffic at multiple points and locate problems immediately. In hardware, fault tolerance is achieved by component and subsystem redundancy.

III. RELATED WORK There are two types of ABE are depending on which of private keys or cipher texts that access policies are associated with. In a key-policy attribute-based encryption (KP-ABE) system, cipher texts are labelled by the transmitter with a set of descriptive attributes, while exploiter's private key is issued by the trusted attribute sway captures a policy (also called the access structure) that specifies which type of cipher texts the key can decrypt. KP-ABE schemes are suitable for structured organizations with rules about who may read particular documents. Typical applications of KP-ABE include secure forensic analysis and target broadcast. For example, in a secure forensic analysis system, audit log entries could be annotated with attributes such as the name of the exploiter, the date and time of the exploiter action, and the type of data modified or accessed by the exploiter action. While a forensic analyst charged with some investigation would be issued a private key that associated with a particular access structure. The private key would only open audit log records whose attributes satisfied the access policy associated with the private key[4], [7],[15]. In a cipher text-policy attribute-based encryption (CP-ABE) system, when a transmitter encrypts a message, they specify a specific access policy in terms of the access structure over attributes in the cipher text,

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stating what kind of receivers will be able to decrypt the cipher text. Exploiters possess sets of attributes and obtain corresponding secret attribute keys from the attribute sway. Such an exploiter can decrypt a cipher text if his/her attributes satisfy the access policy associated with the cipher text. Thus, CP-ABE mechanism is conceptually closer to traditional role-based access control method. 1) Attribute Revocation: Bethencourt et al. [10] and Boldyreva et al. [10] first suggested key revocation mechanisms in CP-ABE and KP-ABE, respectively. Their solutions are to append to each attribute an expiration date (or time) and distribute a new set of keys to valid exploiters after the expiration. The periodic attribute revocable ABE schemes [8][13],[16],[17] have two main problems. The first problem is the security degradation in terms of the backward and forward secrecy. It is a considerable scenario that exploiters such as soldiers may change their attributes frequently, e.g., position or location move when considering these as attributes [4], [9]. Then, a exploiter who newly holds the attribute might be able to access the previous data encrypted before he obtains the attribute until the data is re-encrypted with the newly updated attribute keys by periodic rekeying (backward secrecy). The other is the scalability problem. The key sway periodically announces a key update material by unicast at each time-slot so that all of the nonrevoked exploiters can update their keys. 2) Key Escrow: Most of the existing ABE schemes are constructed on the architecture where a single trusted sway has the power to generate the whole private keys of exploiters with its master secret information [11]. Thus, the key escrow problem is inherently such that the key sway can decrypt every cipher-text addressed to exploiters in the system by generating their secret keys at any time. 3) Decentralized ABE: Huang et al. [9] and Roy et al. [4] proposed decentralized CP-ABE schemes on the multisway network environment. They achieved a combined access policy over the attributes issued by different sway by simply encrypting data multiple times. The main disadvantages of this approach are efficiency and expressiveness of access policy.

IV. DESIGN PRINCIPLES In this section, we describe the DTN architecture and define the security model.

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Fig. 1. Architecture transmission in defense network

secure

data

A. System Description and Assumptions Fig. 1 shows the layout of the DTN. As shown in Fig. 1, the design consists of the following system entities. 1) Key Sway: They are key generation centers that generate public/secret guidelines for CP-ABE. The key sway consists of a central domination and multiple local domination. We assume that there are secure and reliable transmission ducts between a central domination and each local domination during the preliminary key conformation and generation phase. Each local sway manages different attributes and issues corresponding attribute keys to exploiters. They grant different access entitlement to individual exploiters based on the exploitersâ&#x20AC;&#x2122; attributes. The key sway is undertaking to be righteous-but-peculiar. That is, they will honestly perform the assigned tasks in the given order; however they would like to learn information of encrypted contents as much as possible. 2) Supply node: This is an entity that supplies data from transmitters and provide corresponding access to exploiters. It may be dynamic or static [4], [5]. Similar to the previous schemes, we also assume the supply node to be semi-devoted, which is righteous-but-peculiar. 3) Transmitter: This is an entity that has the trusted messages or data (e.g., a commander) and wishes to store them into the exterior data supply node for ease of apportioning or for trustworthy delivery to exploiters in the extreme networking environs. A transmitter is credible for describing (attribute based) access policy and enforcing it on its own data by encrypting the information under the policy before storing it to the supplied node. 4) Exploiter: This is a moving node that needs to gain access the data stored at the supplied node (e.g., a soldier). If an exploiter possesses a set of attributes satisfying the access policy of the encrypted data defined by the transmitter, and is not revoked in any of the attributes, then he will be able to decrypt the cipher text and obtain the data. Since the key sway is semi-trusted, they should be deterred from accessing plaintext of the data in the supply node; meanwhile, they should be still able to issue secret keys to exploiters. In order to realize this somewhat

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contradictory requirement, the central sway and the local sway engage in the arithmetic 2PC protocol with master keys of their own and issue independent key components to exploiters during the key issuing phase. The 2PC protocol prevents them from knowing each other’s master secrets so that none of them can generate the whole set of secret keys of exploiters individually. Thus, we take an assumption that the central sway does not collude with the local sway (otherwise, they can guess the secret keys of every exploiter by sharing their master secrets). B. Security Requirements 1) Data confidentiality: Unauthorized exploiters who do not have enough credentials satisfying the access policy should be deterred from accessing the plain data in the supply node. In addition, unauthorized access from the supply node or key sway should also be prevented. 2) Collusion-resistance: If multiple exploiters collude, they may be able to decrypt a cipher text by combining their attributes even if each of the exploiters cannot decrypt the cipher text alone. For example, suppose there exist a exploiter with attributes {”Battalion 1”, “Region 1”} and another exploiter with attributes {”Battalion 2”, “Region 2”}. They may succeed in decrypting a cipher text encrypted under the access policy of (“Battalion 1” AND “Region 2”), even if each of them cannot decrypt it individually. We do not want these colluders to be able to decrypt the secret information by combining their attributes. We also consider a collusion attack among curious local sway to derive exploiters’ keys. 3) Backward and forward Secrecy: In the context of ABE, backward secrecy means that any exploiter who comes to hold an attribute (that satisfies the access policy) should be prevented from accessing the plaintext of the previous data exchanged before he holds the attribute. On the other hand, forward secrecy means that any exploiter who drops an attribute should be prevented from accessing the plaintext of the subsequent data exchanged after he drops the attribute, unless the other valid attributes that he is holding satisfy the access policy.

III. PRELIMINARIES Cryptographic Background We first provide a formal definition for access structure recapitulating the definitions in [12] and [13]. Then, we will briefly review the necessary facts about the bilinear map and its security assumption. 1) Access Structure: Let {P1,P2,……,Pn} be a set of parties. A collection Ḁ is a subset of 2{P1, P2,…….., Pn} is monotone. An access structure (respectively, monotone access structure) is a collection (respectively, monotone collection) Ḁ of nonempty subsets of {P1,P2,……,Pn}.The sets Ḁ in are called the authorized sets, and the sets not Ḁ in are called the unauthorized sets. 2) Bilinear Pairings: Let G0 and G1 be a multiplicative

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cyclic group of prime order p. Let g be a generator of G0. A map e: G0 * G1→G1 is said to be bilinear. 3)Bilinear Diffie–Hellman Assumption: Using the above notations, the Bilinear Diffie–Hellman (BDH) problem is to compute e (g,g)abcԑ G1 given a generator g of G0 and elements ga, gb ,gc for a,b,c. An equivalent formulation of the BDH problem is to compute e(A,B)c given a generator g of G0, and elements A,B and gc in G0.

IV. CIPHER-TEXT POLICY In this section, we provide a multisway CP-ABE scheme for secure data transmission DTNs. Each local sway issue partial personalized and attribute key components to an exploiter by performing secure 2PC protocol with the central sway. Each attribute key of an exploiter can be updated individually and immediately. Thus, the scalability and security can be enhanced in the proposed scheme. A. Access Tree 1) Description: Let be a tree representing an access structure. Each non leaf node of the tree represents a threshold gate. If is the number of children of a node x and k ͯ is its threshold value, then 0 ≤ kx ≤ numx. Each leaf node x of the tree is described by an attribute and a threshold value kx=1. 2) Satisfying an Access Tree: Let Ʈx be the sub tree of Ʈ rooted at the node x. If a set of attributes γ satisfies the access Tree Ʈx, we denote it as Ʈx(γ)=1. B. Scheme Construction Let G0 be a bilinear group of prime order , and let be a generator of G0. Let e : G0 * G0→G1 denote the bilinear map. A security parameter k, will determine the size of the groups. 1) System Setup: At the initial system setup phase, the trusted initializer2 chooses a bilinear group G0 of prime order with generator according to the security parameter. It also chooses hash functions H:{0,1}* ->G0 from a family of universal one-way hash functions. The public parameter param is given by (G0,g,H). Central Key Sway: CA chooses a random exponent β€R Ƶ*р. The master public/private key pair is given by (PK cᴀ = h¸ МK cᴀ= β) Local Key Sway: Each Ai chooses a random exponent αᶤ ε R Ƶ*P. The master public/private key pair is given by (PK ᴀi = e(g¸g)α ͥ¸ МK ᴀi= α ͥ) 2) Key Generation: In CP-ABE, exploiter secret key components consist of a single personalized key and multiple attribute keys. The personalized key is uniquely determined for each exploiter to prevent collusion attack among exploiters with different attributes. The proposed key generation protocol is composed of the personal key generation followed by the attribute key generation protocols. It exploits arithmetic secure 2PC protocol to eliminate the key escrow problem such that none of the

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sway can determine the whole key components of exploiters individually. During the key generation phase using the 2PC protocol, the proposed scheme (especially 2PC protocol) requires (3m + 1)C0 messages additively to the key issuing overhead in the previous multisway ABE schemes in terms of the communication cost, where m is the number of key sway the exploiter is associated with, and C0 is the bit size of an element in G0. However, it is important to note that the 2PC protocol is done only once during the initial key generation phase for each exploiter. Therefore, it is negligible compared to the communication overhead for encryption or key update, which could be much more frequently performed in the networks. C. Revocation We observed that it is impossible to revoke specific attribute keys of a exploiter without rekeying the whole set of key components of the exploiter in ABE key structure since the whole key set of a exploiter is bound to the same random value in order to prevent any collusion attack. Therefore, revoking a single attribute in the system requires all exploiters who share the attribute to update all their key components even if the other attributes of them are still valid. This seems very inefficient and may cause severe overhead in terms of the computation and communication cost, especially in large-scaled networks. One promising way to immediately revoke an attribute of specific exploiters is to re-encrypt the ciphertext with each attribute group key and selectively distribute the attribute group key to authorized (nonrevoked) exploiters who are qualified with the attribute. Before distributing the cipher-text, the supply node receives a set of membership information for each attribute group G that appears in the access tree of CT from the corresponding sway and re-encrypts it as follows. Generates a header message where each contains the encrypted attribute group keys , which could be only decrypted by non revoked attribute group members. This can be done by exploiting many previous stateful or stateless group key handler schemes. We will adopt the complete sub tree method, which requires each exploiter to store additional key encryption keys (KEKs). The header message would be at most sizes for each attribute group, where and are the number of all exploiters in the system and that of exploiters in the attribute group, respectively. D. Key Update When a exploiter comes to hold or drop an attribute, the corresponding key should be updated to prevent the exploiter from accessing the previous or subsequent encrypted data for backward or forward secrecy, respectively. The key update procedure is launched by sending a join or leave request for some

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attribute group from a exploiter who wants to hold or drop the attribute to the corresponding sway. On receipt of the membership change request for some attribute groups, it notifies the supply node of the event. Without loss of generality, suppose there is any membership change in Gi.

V. ANALYSIS In this section, we first analyze and compare the efficiency of the proposed scheme to the previous multisway CP-ABE schemes in theoretical aspects. Then, the efficiency of the proposed scheme is demonstrated in the network simulation in terms of the communication cost. We also discuss its efficiency when implemented with specific parameters and compare these results to those obtained by the other schemes. A. Efficiency The logic expressiveness of access structure that can be defined under different disjoint sets of attributes (managed by different sway), key escrow, and revocation granularity of each CP-ABE scheme. Here the logic can be very expressive as in the single sway system like BSW[13] such that the access policy can be expressed with any monotone access structure under attributes of any chosen set of sway; while HV[9] and RC[4] schemes only allow the AND gate among the sets of attributes managed by different sway. The revocation can be done in an immediate way as opposed to BSW. Therefore, attributes of exploiters can be revoked at any time even before the expiration time that might be set to the attribute. B. Simulation In this simulation, we consider DTN applications using the Internet protected by the attribute-based encryption. Network Simulator NS2 is a primer providing materials for NS2 beginners, whether students, professors, or researchers for understanding the architecture of Network Simulator 2 (NS2) and for incorporating simulation modules into NS2. The authors discuss the simulation architecture and the key components of NS2 including simulation-related objects, network objects, packet-related objects, and helper objects. The NS2 modules included within are nodes, links, Simple link objects, packets, agents, and applications. Further, the book covers three helper modules: timers, random number generators, and error models. Also included are chapters on summary of debugging, variable and packet tracing, result compilation, and examples for extending NS2. Two appendices provide the details of scripting language Tcl, OTcl and AWK, as well object oriented programming used extensively in NS2.

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VI. SECURITY In this section, we prove the security of our scheme with regard to the security requirements

Fig. 2. Number of exploiters in an attribute group. Fig. 2 represents the number of current exploiters and revoked exploiters in an attribute group during 100 h.

Fig. 3. Communication cost in the multisway CP-ABE systems. Fig. 3 shows the total communication cost that the transmitter or the supply node needs to send on a membership change in each multi sway CP-ABE scheme. It includes the cipher text and rekeying messages for nonrevoked exploiters. It is measured in bits. In this simulation, the total number of exploiters in the network is 10 000, and the number of attributes in the system is 30. The number of the key sway is 10, and the average number of attributes associated with a exploiter’s key is 10. C. Implementation Next, we analyze and measure the computation cost for encrypting (by a transmitter) and decrypting (by an exploiter) a data. We used a Type-A curve (in the pairing-based cryptography (PBC) library providing groups in which a bilinear map e : G0 * G0→G1 is defined. Although such curves provide good computational efficiency (especially for pairing computation), the same does not hold from the point of view of the space required to represent group elements. Indeed, each element of G0 needs 512 bits at an 80-bit security level and 1536 bits when 128-bit of security

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A. Collusion Resistance In CP-ABE, the secret sharing must be embedded into the Cipher text instead to the private keys of exploiters. Like the previous ABE schemes, the private keys (SK) of exploiters are randomized with personalized random values selected by the CA such that they cannot be combined in this scheme. Another collusion attack scenario is the collusion between revoked exploiters in order to obtain the valid attribute group keys for some attributes that they are not authorized to have (e.g., due to revocation). The attribute group key distribution protocol, which is a complete sub tree method in the proposed scheme, is secure in terms of the key indistinguishability. Thus, the colluding revoked exploiters can by no means obtain any valid attribute group keys for attributes that they are not authorized to hold. B. Data Confidentiality In our trust model, the multiple key sway are no longer fully trusted as well as the supply node even if they are honest. Therefore, the plain data to be stored should be kept secret from them as well as from unauthorized exploiters. Data confidentiality on the stored data against unauthorized exploiters can be trivially guaranteed. If the set of attributes of an exploiter cannot satisfy the access tree in the cipher text, he cannot recover the desired value e (g, g)rs during the decryption process, where r is a random value uniquely assigned to him. Another attack on the stored data can be launched by the supply node and the key sway. Since they cannot be totally trusted, confidentiality for the stored data against them is another essential security criteria for secure data retrieval in DTNs. The local sway issue a set of attributes keys for their managing attributes to an authenticated exploiter, which are blinded by secret information that is distributed to the exploiter from CA. They also issue the exploiter a personalized, secret key by performing the secure 2PC protocol with CA. The key generation protocol discourages each party to obtain each other’s master secret key and determine the secret key issued from each other. Therefore, they could not have enough information to determine the whole set of secret key of the exploiter individually. Even if the supply node manages the attribute group keys, it cannot decrypt any of the nodes in the access tree in the cipher text. This is because it is only authorized to re-encrypt the cipher text with each attribute group key, but is not allowed to decrypt it (that is, any of the key components of exploiters are not given to the node). Therefore, data confidentiality

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against the curious key sway and supply node is also ensured. C. Backward and Forward Secrecy When an exploiter comes to hold a set of attributes that satisfy the access policy in the cipher text at some time instance, the corresponding attribute group keys are updated and delivered to the valid attribute group members securely (including the exploiter). In addition, all of the components encrypted with a secret key in the cipher text are re-encrypted by the supply node with a random, and the cipher text components corresponding to the attributes are also re-encrypted with the updated attribute group keys. Even if the exploiter has stored in the previous cipher text exchanged before he obtains the attribute keys and the holding attributes satisfy the access policy, he cannot decrypt the pervious cipher text. On the other hand, when an exploiter comes to drop a set of attributes that satisfy the access policy at some time instance, the corresponding attribute group keys are also updated and delivered to the valid attribute group members securely (excluding the exploiter). Then, all of the components encrypted with a secret key in the cipher text are re encrypted by the supply node with a random , and the cipher text components corresponding to the attributes are also re-encrypted with the updated attribute group keys. Then, the exploiter cannot decrypt any nodes corresponding to the attributes after revocation due to the blindness resulted from newly updated attribute group keys. In addition, even if the exploiter has recovered e(g ,g)(ɑ1+.......+ɑm)s before he was revoked from the attribute groups and stored it, it will not help to decrypt the subsequent cipher text e(g ,g)(ɑ1+.......+ɑm)(s+s´) re-encrypted with a new random . Therefore, the forward secrecy of the stored data is guaranteed in this scheme.

VII. CONCLUSION DTN technologies are becoming successful solutions in military applications that allow wireless devices to communicate with each other and access the confidential information reliably by exploiting external supply nodes. CP-ABE is a scalable cryptographic solution to the access control and secures data retrieval issues. In this paper, we proposed an efficient and secure data retrieval method using CP-ABE for decentralized DTNs where multiple key sway manages their attributes independently. The inherent key escrow problem is resolved such that the confidentiality of the stored data is guaranteed even under the hostile environment where key sway might be compromised or not fully trusted. In addition, the fine-grained key revocation can be done for each attribute group. We demonstrate how to apply the proposed mechanism to securely and efficiently manage the confidential data distributed in the disruption-tolerant defese network.

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REFERENCES [1] J. Burgess, B. Gallagher, D. Jensen, and B. N. Levine, “Maxprop: Routing for vehicle-based disruption tolerant networks,” 2006, [2] M. Chuah and P. Yang, “Node density-based adaptive routing scheme for disruption tolerant networks,” 2006,. [3] M. M. B. Tariq, M. Ammar, and E. Zequra, “Mesage ferry route design for sparse ad hoc networks with mobile nodes,” in Proc. ACM MobiHoc, 2006,. [4] S. Roy andM. Chuah, “Secure data retrieval based on ciphertext policy attribute-based encryption (CP-ABE) system for the DTNs,” Lehigh CSE Tech. Rep., 2009. [5] M. Chuah and P. Yang, “Performance evaluation of content-based information retrieval schemes for DTNs, 2007 [6] M. Kallahalla, E. Riedel, R. Swaminathan, Q. Wang, and K. Fu, “Plutus: Scalable secure file sharing on untrusted storage,” 2003 [7] L. Ibraimi, M. Petkovic, S. Nikova, P. Hartel, and W. Jonker, “Mediated ciphertext-policy attribute-based encryption and its application,” 2009. [8] N. Chen, M. Gerla, D. Huang, and X. Hong, “Secure, selective group broadcast in vehicular networks using dynamic attribute based encryption,” 2010 [9] D. Huang and M. Verma, “ASPE: Attribute-based secure policy enforcement in vehicular ad hoc networks,” 2009 [10] A. Lewko and B. Waters, “Decentralizing attributebased encryption,” Cryptology ePrint Archive: Rep. 2010/351, 2010 [11] A. Sahai and B. Waters, “Fuzzy identity-based encryption,” in Proc. Eurocrypt, 2005 [12] V. Goyal, O. Pandey, A. Sahai, and B. Waters, “Attribute-based encryption for fine-grained access control of encrypted data,”2006 [13] J. Bethencourt, A. Sahai, and B. Waters, “Ciphertext-policy attributebased encryption,” 2007, [14] R. Ostrovsky, A. Sahai, and B. Waters, “Attributebased encryption with non-monotonic access structures,” 2007. [15] S. Yu, C. Wang, K. Ren, and W. Lou, “Attribute based data sharing with attribute revocation,” 2010, pp. [16] A. Boldyreva, V. Goyal, and V. Kumar, “Identitybased encryption with efficient revocation2008, [17] M. Pirretti, P. Traynor, P. McDaniel, and B. Waters, “Secure attribute based systems,” 2006

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Load Stabilizing and Energy Conserving Routing Protocol for Wireless Sensor Networks Janakiraman V. M.E(Computer Science and Engineering) Sree Sowdambika College of Engineering Aruppukottai, Tamilnadu, India.

Mr. G.Vadivel Murugan M.E., Assistant Professor Dept of Computer Science and Engineering Sree Sowdambika College of Engineering Aruppukottai, Tamilnadu, India.

Abstract— Wireless sensor network (WSN) is a system consists of a massive collection of low-cost micro-sensors. WSN is used to gather and send various types of the messages to a base station (BS). WSN consists of low-cost nodes with limited battery capacity, and replacement of the battery is not easy for WSN with thousands of physically connected nodes, which means energy conserving routing protocol should be employed to offer a long-life work time. To accomplish the aim, we need not only to minimize total energy utilization but also to balance WSN load. Research workers have recommended many protocols such as LEACH, HEED, TBC, PEGASIS and PEDAP. In this paper, we suggest a Load Stabilizing Tree Based Energy Conserving Routing Protocol(LSTEC ) which constructs a routing tree using a process where as each round BS assigns a root node and transmits this selection to all sensor nodes. Eventually, each node chooses its parent by contemplating only itself and its neighbors' information, thus making LSTEC a dynamic protocol. Simulation results show that LSTEC has a better performance than other protocols in balancing energy utilization, thus extending the lifetime of WSN. Keywords—Energy utilization, Load balance, Network lifetime, Routing protocol, Tree based, Wireless Sensor Network.

I. INTRODUCTION Generally, wireless sensor nodes are located arbitrarily and tightly coupled in a target area, especially where the physical environment is too hard that the macrosensor counterparts cannot be deployed. After deployment, if there is no sufficient battery power, the network cannot work properly [1], [2], [3]. In general, WSN may generate quite a large amount of data, so if data fusion could be used, the throughput could be decreased [4]. Because sensor nodes are deployed densely, WSN might produce redundant data from multiple nodes, and the redundant data can be unified to reduce communication. Many familiar protocols execute data fusion, but almost all of them suppose that the length of the message dispatched by each relay node should be constant, i.e., each node sends the same amount of data no matter how much data it sustains from its child nodes[10]. PEDAP [7] and PEGASIS [8] are conventional protocols based on this supposition and perform far better than HEED and LEACH in this case. However, there are quite a few applications in which the length of the message transferred by a parent node depends not only on the length of its own, but also on the length of the messages received from its child nodes [10].

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Mr. M.Senthil Kumar M.Tech., Assistant Professor Dept of Computer Science and Engineering Sree Sowdambika College of Engineering Aruppukottai, Tamilnadu, India.

Energy consumption of a node is due to either “useful” or "wasteful" operations. The useful operations include transmitting or receiving data messages, and processing requests. On the other hand, the wasteful consumption is due to the operation of routing tree construction, overhearing, retransmitting because of rasping environment, and dealing with redundant broadcast overhead messages. In this paper, we propose Load Stabilizing Tree Based Energy Conserving Routing Protocol (LSTEC).We contemplates a situation in which the network collects data periodically from a location where each node continuously senses the environment and sends the data back to BS [9]. In General there are two definitions for network lifetime: a) The starting time of the network operation to the death of the first node in the network [8]. b) The starting time of the network operation to the death of the last node in the network. In this paper, we agree with the first definition. Moreover, we consider two exceptional cases in data fusion: Case (1) The data between any sensor nodes can be fused totally. Each node sends the same volume of data that does not matter how much data it receives from its child nodes. Case (2) The data cannot be fused. The length of the message transmitted by each relay node is the sum of its own sensed data and received data from its child nodes. The rest of the paper is categorized as follows: Section II related works. The radio models and network of our proposal are discussed in Section III. Section IV describes the detailed architecture of LSTEC. In Section V we show our simulations varied to the simulations of other protocols. Finally, Section VI conclusion. II. RELATED WORKS A major task of WSN is to collect information periodically from the preferred area and transmit the information to BS. A simple method to attain this task is that each sensor node transmits data directly to BS. However, when BS is sited a long away from the target area, the sensor nodes will die rapidly due to more energy utilization. On the other hand, since the gap between each node and BS are different, direct transmission may lead to unbalanced energy consumption. To solve these problems, many protocols have been proposed such as LEACH, PEGASIS, HEED, PEDAP.

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Proceedings of International Conference on Advancements in Engineering and Technology In LEACH [4], [5], for the entire network, nodes are selected according to a fraction p from all sensor nodes are fixed to serve as cluster heads (CHs), where p is a design parameter. The operations of LEACH are split into several rounds. Each round includes a design phase and a static-state phase. During the design phase, each node will decide whether to be a CH or not according to a predefined specification. After CHs are selected, each of other nodes will choose its own CH and join the cluster according to the power of many received messages. Each node will choose the nearest CH. During the static-state phase, CHs fuse the data received from their cluster nodes and send the fused data to BS by single-hop connection. LEACH uses randomization to turn around CHs for each round in order to consistently allocate the energy consumption. So LEACH can minimize the amount of data directly broadcasted to BS and balance WSN load, thus attaining a factor of 8 times growth compared with direct transmission. In [6], the authors proposed a hybrid, energyefficient, distributed clustering algorithm (HEED). HEED is an enhancement of LEACH on the method of CH choosing. In each round, HEED selects CHs according to the remaining energy of each node and a secondary parameter such as nodes proximity to their neighbors or nodes degrees. By iterations and competition, HEED ensures only one CH within a certain range, so uniform CHs distribution is achieved across the network. Compared with LEACH, HEED effectively prolongs network lifetime and is suitable for situations such as where each node has different initial energy. For Case1, LEACH and HEED greatly reduce total energy consumption. However, LEACH and HEED consume energy heavily in the head nodes, which makes the head nodes die quickly. S. Lindsey et al. proposed an algorithm related to LEACH and it is called PEGASIS [7]. PEGASIS is a nearly optimal power efficient protocol which uses GREEDY algorithm to make all the sensor nodes in the network form a chain. In PEGASIS, the (i mod N)th node is chosen to be a leader and the leader is the only one which needs to communicate with BS in round i. N is the total amount of nodes. Data is collected by starting from both endpoints of the chain, and transmitted along the chain, and fused each time it transmits from one node to the next until it reaches the leader. So PEGASIS sharply reduces the total amount of data for long-distance transmission and achieves a better performance than LEACH by 100% to 300% in terms of network lifetime. III. NETWORK AND RADIO MODEL In our work, we assume that the system model has the following properties:  Sensor nodes are randomly distributed in the square field and there is only one BS deployed far away from the area.  Sensor nodes are stationary and energy constrained. Once deployed, they will keep operating until their energy is exhausted.  BS is stationary, but it is not energy constrained.

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

All sensor nodes have power control capabilities; each node can change the power level and communicate with BS directly.  Sensor nodes are location-aware. A sensor node can get its location information through other mechanisms such as GPS or position algorithms.  Each node has its unique identifier (ID). For both cases, the medium is assumed to be symmetric so that the energy required for transmitting a message from node A to node B or from node B to node A is the same. IV. LOAD STABILIZING TREE BASED ENERGY CONSERVING PROTOCOL The main aim of LSTEC is to achieve a longer network lifetime for different applications. In each round, BS assigns a root node and broadcasts its ID and its coordinates to all sensor nodes. Then the network computes the path either by transmitting the path information from BS to sensor nodes or by having the same tree structure being dynamically and individually built by each node. For both cases, LSTEC can change the root and reconstruct the routing tree with short delay and low energy consumption. Therefore a better balanced load is achieved compared with the protocols mentioned in Section II. The operation of LSTEC is divided into Initial Phase, Tree Construction Phase, Data Collection and Transmission Phase, and Information Exchange Phase. A. Initial Phase In Initial Phase, the network parameters are initialized. Initial Phase is divided into three steps. Step 1: When Initial Phase begins, BS broadcasts a packet to all the nodes to inform them of beginning time, the length of time slot and the number of nodes N. When all the nodes receive the packet, they will compute their own energy-level (EL) using function: EL is a parameter for load balance. Step 2: Each node sends its packet in a circle with a certain radius during its own time slot after Step 1. For example, in the time slot, the node whose ID is I will send out its packet. This packet contains a preamble and the information such as coordinates and EL of node i. All the other nodes during this time slot will monitor the channel, and if some of them are the neighbors of node i, they can receive this packet and record the information of node i in memory. After all nodes send their information, each node records a table in their memory which contains the information of all its neighbors. Step 3: Each node sends a packet which contains all its neighbors’ information during its own time slot when Step 2 is over. Then its neighbors can receive this packet and record the information in memory. The length of time slots in Steps 2 and 3 is predefined,

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Proceedings of International Conference on Advancements in Engineering and Technology thus when time is up, each node has sent its information before Initial Phase ended. After Initial Phase, each node records two tables in memory which contain the information of all its neighbors and its neighbors’ neighbors. These two tables are defined as Table I and Table II. B. Tree Construction Phase Within each round, LSTEC performs the following steps to build a routing tree. Between Case1 and Case2 there are some differences in the steps of routing tree constructing: Step 1: BS assigns a node as root and broadcasts root ID and root coordinates to all sensor nodes. TABLE I NETWORK LIFETIMES OF DIFFERENT SCHEMES

For Case1, because data fusion technique is implemented, only one node which communicates directly with BS can transmit all the data with the same length as its own, which results in much less energy consumption. In order to balance the network load for Case1, in each round, a node with the largest residual energy is chosen as root. The root collects the data of all sensors and transmits the fused data to BS over long distance. For Case2, because data can’t be fused, it will not save the energy for data transmitting by making fewer nodes communicate directly with BS. When one of the sensor nodes collects all the data and sends it to BS, it would deplete its energy quickly. In this case BS always assigns itself as root. Step 2: Each node tries to select a parent in neighbors using EL and coordinates which are recorded in Table I. The selection criteria are: 1) For both Case1 and Case2, for a sensor node, the distance between its parent node and the root should be shorter than that between itself and the root. 2) For Case1, each node chooses a neighbor that satisfies criterion 1 and is the nearest to itself as its parent. And if the node can’t find a neighbor which satisfies criterion 1, it selects the root as its parent.

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3) For Case2, the process of Tree Constructing Phase can be regarded as an iterative algorithm. Besides criterion 1, for a sensor node, only the nodes with the largest EL of all its neighbors and itself can act as relay nodes. If the sensor node itself has the largest EL, it can also be considered to be an imaginary relay node. Choosing the parent node from all the relay nodes is based on energy consumptions. Any of these consumptions is the sum of consumption from the sensor node to a relay node and that from the relay node to BS. The relay node which causes minimum consumption will be chosen as the parent node. It is true that this relay node should choose its parent node in the same way. So a path with minimum consumption is found by iterations. And by using EL, LSTEC chooses the nodes with more residual energy to transmit data for long distance. If the sensor node cannot find a suitable parent node, it will transmit its data directly to BS. Step 3: Because every node chooses the parent from its neighbors and every node records its neighbors’ neighbors’ information in Table II, each node can know all its neighbors’ parent nodes by computing, and it can also know all its child nodes. If a node has no child node, it defines itself as a leaf node, from which the data transmitting begins. As discussed above, for Case1, because each packet

sent to the parent nodes will be fused, the minimum energy consumption can be achieved if each node chooses the node nearest to it. But if all nodes choose their nearest neighbors, the network may not be able to build a tree. Fig. 1 shows a network of 100 nodes in this situation. We can find that some

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Proceedings of International Conference on Advancements in Engineering and Technology clusters are formed, but they cannot connect with others. Thus in LSTEC, we use criterion 1 in Case1 to limit the search direction. By this approach, a routing tree is constructed and some nodes still have the possibility of connecting to their nearest neighbors. For Case2, criterion 1 should also be obeyed and this criterion helps to save the energy for data transmitting to a certain extent. To build a routing tree, for Case1, each node follows the steps. But for Case2, we use BS to compute the topography. C. Data Collection and Transmission Phase After the routing tree is constructed, each sensor node collects information to generate a DATA_PKT which needs to be transmitted to BS. For Case1, TDMA and Frequency Hopping Spread Spectrum (FHSS) are both applied. This phase is divided into several TDMA time slots. In a time slot, only the leaf nodes try to send their DATA_PKTs. After a

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node receives all the data from its child nodes, this node itself serves as a leaf node and tries to send the fused data in the next time slot. Each TDMA time slot is divided into three segments as follows (see Fig. 2). Segment1: The first segment is used to check if there is communication interference for a parent node. In this segment, each leaf node sends a beacon which contains its ID to its parent node at the same time. Three situations may occur and they divide all the parent nodes into three kinds. For the first situation, if no leaf node needs to transmit data to the parent node in this time slot, it receives nothing. For the second situation, if more than one leaf node needs to transmit data to the parent node, it receives an incorrect beacon. For the third situation, if only one leaf node needs to transmit data to the parent node, it receives a correct beacon.

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Segment 2: During the second segment, the leaf nodes which can transmit their data are confirmed. For the first situation, the parent node turns to sleep mode until next time slot starts. For the second situation, the parent node sends a control packet to all its child nodes. This control packet chooses one of its child nodes to transmit data in the next segment. For the third situation, the parent node sends a control packet to this leaf node. This control packet tells this leaf node to transmit data in the next segment. Segment 3: The permitted leaf nodes send their data to their parent nodes, while other leaf nodes turn to sleep mode. The process in one time slot is shown in Fig. 2. For Case2, each node chooses its parent by considering not the distance but the total energy consumption. In our simulation results, we will show that there may be many leaf nodes sharing one parent node in one time slot. If all the leaf nodes try to transmit their data at the same time, the data messages sent to the same parent node may interfere with each other. By applying Frequency Division Multiple Access (FDMA) or Code Division Multiple Access (CDMA), the schedule generated under competition is able to avoid collisions. However, the accompanying massive control packets will cause a large amount of energy to be wasted. Thus the process may be much simpler. At the beginning of each round, the operation is also divided into several time slots. In the ith time slot, the node whose ID is i turns on its radio and receives the message from BS. BS uses the same approach to construct the routing tree in each round, and then BS tells sensor nodes when to send or receive the data. D. Information Exchange Phase For Case1, since each node needs to generate and transmit a DATA_PKT in each round, it may exhaust its energy and die. The dying of any sensor node can influence the topography. So the nodes that are going to die need to inform others. The process is also divided into time slots. In each time slot, the nodes whose energy is going to be exhausted will compute a random delay which makes only one node broadcast in this time slot. When the delay is ended, these nodes are trying to broadcast a packet to the whole network. While all other nodes are monitoring the channel, they will receive this packet and perform an ID check. Then they modify their tables. If no such packet is received in the time slot, the network will start the next round. For Case2, BS can collect the initial EL and coordinates information of all the sensor nodes in Initial Phase. For each round, BS builds the routing tree and the schedule of the network by using the EL and coordinates information. Once the routing tree is built, the energy consumption of each sensor node in this round can be calculated by BS, thus the information needed for calculating the topology for the next round can be known in advance. However, because WSN may be deployed in an unfriendly environment, the actual EL of each sensor node may be different from the EL calculated by BS. To cope with this problem, each sensor node calculates its EL and

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detects its actual residual energy in each round. We define the calculated EL as EL1 and the actual EL as EL2. When the two ELs of a sensor node are different, the sensor node generates an error flag and packs the information of actual residual energy into DATA_PKT, which needs to be sent to BS. When this DATA_PKT is received, BS will get the actual residual energy of this sensor node and use it to calculate the topology in the next round. V. COMPARATIVE ANALYSIS AND SIMULATION RESULTS A MATLAB simulation of LSTEC is done for both Case1 and Case2 to evaluate the performance. For Case1, we first compare LSTEC with PEGASIS and use the same network model as PEGASIS. We generate a randomly distributed 100 to 400 nodes network of square area 100 m Ă&#x2014; 100 m with BS located at (50 m, 175 m) and use DATA_PKT length of 2000 bits and

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Proceedings of International Conference on Advancements in Engineering and Technology CTRL_PKT length of 100 bits. We let each node have 0.25 J initial energy. Fig. 3 and Fig. 4 show the routing tree generated by LSTEC and PEGASIS for exactly the same 100 node topology. In Fig. 3 the triangle is root node and in Fig. 4 the triangle is head node and the rectangle is tail node. As seen, the routing tree generated by LSTEC is better. Since PEGASIS uses GREEDY algorithm to form a chain, long links may exist between parent nodes and child nodes, which will cause an unbalanced load. As for LSTEC, each node tends to choose the nearest neighbor to avoid long links. Fig. 5 shows that the time when the first node dies changes within a range from 100 nodes to 400 nodes in the network. We can find that LSTEC performs much better than PEGASIS and prolongs network lifetime by about 100% to 300% in Fig. 5.

Fig. 5. For Case1, we compare the time when first node dies for GSTEB and PEGASIS for the number of nodes from 100 to 400.

Fig. 6. For Case1, we compare the time when first node dies for GSTEB and HEED for the number of nodes from 100 to 400.

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In Fig. 6 shows that the time when the first node dies changes within a range from 100 nodes to 400 nodes in the network. Clearly, LSTEC performs better than HEED and prolongs the network lifetime by more than 100%. VI. CONCLUSIONS In this work, we introduce LSTEC. Two definitions of network lifetime and two extreme cases of data fusion are proposed. The simulations show that when the data collected by sensors is strongly correlative, LSTEC outperforms LEACH, PEGASIS and HEED. Because LSTEC consumes only a small amount of energy in each round to change the topography for the purpose of balancing the energy consumption. All the leaf nodes can transmit data in the same TDMA time slot so that the transmitting delay is short. When lifetime is defined as the time from the start of the network operation to the death of the first node in the network, LSTEC prolongs the lifetime by 100% to 300% compared with PEGASIS. In some cases, we are more interested in the lifetime of the last node in the network. Some slight changes are made to make the performance of LSTEC similar to that of PEDAP. So LSTEC is nearly the optimal solution in Case1. When the data collected by sensors cannot be fused, LSTEC offers another simple approach to balancing the network load. In fact, it is difficult to distribute the load evenly on all nodes in such a case. Even though LSTEC needs BS to compute the topography, which leads to an increase in energy waste and a longer delay, this kind of energy waste and longer delay are acceptable when compared with the energy consumption and the time delay for data transmitting. Simulation results show that when lifetime is defined as the time from the start of the network operation to the death of the first node in the network, LSTEC prolongs the lifetime of the network by more than 100% compared with HEED. REFERENCES [1] K. Akkaya and M. Younis, “A survey of routing protocols in wireless sensor networks,” Elsevier Ad Hoc Network J., vol. 3/3, pp. 325–349, 2005. [2] I. F. Akyildiz et al., “Wireless sensor networks: A survey,” Computer Netw., vol. 38, pp. 393–422, Mar. 2002. [3] K. T. Kim and H. Y. Youn, “Tree-Based Clustering(TBC) for energy efficient wireless sensor networks,” in Proc. AINA 2010, 2010, pp. 680–685. [4] M. Liu, J. Cao, G. Chen, and X.Wang, “An energy-aware routing protocol in wireless sensor networks,” Sensors, vol. 9, pp. 445–462, 2009. [5] W. Liang and Y. Liu, “Online data gathering for maximizing network lifetime in sensor networks,” IEEE Trans Mobile Computing, vol. 6, no. 1, pp. 2–11, 2007. [6] O. Younis and S. Fahmy, “HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks,” IEEE Trans. Mobile Computing, vol. 3, no. 4, pp. 660–669, 2004. [7] S. Lindsey and C. Raghavendra, “Pegasis: Power-efficient gathering in sensor information systems,” in Proc. IEEE Aerospace Conf., 2002, vol. 3, pp. 1125–1130. [8] H. O. Tan and I. Korpeoglu, “Power efficient data gathering and Aggregation in wireless sensor networks,” SIGMOD Rec., vol. 32, no. 4, pp. 66–71, 2003. [9] G. Mankar and S. T. Bodkhe, “Traffic aware energy efficient routing protocol,” in Proc. 3rd ICECT, 2011, vol. 6, pp. 316–320, . [10] R. Szewczyk, J. Polastre, A.Mainwaring, and D. Culler, “Lessons from sensor network expedition,” in Proc. 1st European Workshop on Wireless Sensor Networks EWSN ‘04, Germany, Jan. 19-21, 2004.

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Multi-View and Multi Band Face Recognition Survey Ms.L.MadhuMitha PG Student, CSE Dept Velammal Engineering College lmadhuviet@gmail.com

Ms. A.BhagyaLakshmi Asst.Prof, CSE Dept Velammal Engineering College kirubhagya@yahoo.com

Abstract - Face recognition is a challenging problem for security surveillance and become an active research area during few decades. Due to the different levels of illumination conditions, variations due to lighting, expression and aging, the recognition of such algorithms rate is considerably limited. To solve this problem,multi-band face recognition algorithm is introduced in this paper. The multi-view and multi band face recognition used in this paper is suitable for estimation the pose of the face from a video source. Unlike previous eigenface or PCA approach, a small number (40 or lower) of eigenfaces are derived from a set of training face images by using the Karhunen-Loeve transform or PCA. Instead, the similarity between feature sets from different videos using Wavelet Transform, Entropy imaging is measured in this work. The experimental results show that the wavelet transform takes less response time which is more suitable for feature extraction and face matching with high accuracy, performance and accuracy in CBIR system. Keywords: Image Processing, Face Recognition, Multi-View Videos, Wavelet Transform.

I. Introduction A biometric system[4] provides automatic recognition of an individual based on some sort of unique feature or characteristic possessed by the individual. Behavioral biometrics includes signatures, voice recognition, gait measurement, and keystroke recognition. Physiological biometrics includes facial recognition, fingerprinting, hand profiling, iris recognition, retinal scanning, and DNA testing. Behavioral methods tend to be less reliable than physiological methods because they are easier to duplicate than physical characteristics (Jain et al., 1999). Physiological attributes are more trusted method in biometrics among which iris recognition is gaining much attention in accuracy and reliability. First automatic face recognition[2][3][5] system was Developed by Kanade 1973. A face recognition system is expected to identify faces present in images and videos automatically. It can operate in either or both of two modes: Face verification (or authentication): involves a one-toone match that compares a query face image against a template face image whose Identity is being claimed. Face identification (or recognition)[8][9]: involves One-to-many matches that compare a Query face image against all the template images in the database to determine the identity of the query face. During face recognition major challenges is Inter-class similarity and Intraclass similarity. Inter-class similarity means people having identified similar faces which make their

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distinction difficult. And Intra-class variations Causes some changes in head pose, illumination conditions, expressions, facial accessories, expressions, aging effects. Lighting conditions change the face appearances so approaches based on intensity images are not sufficient for overcoming this problem. II. Background concepts A. Feature Recognition: Biometric facial recognition systems[1][7] compare images of individuals from incoming video against specific databases and send alerts when a positive match occurs. The key steps in facial recognition are: face detection, recording detected faces, Match recorded faces with those stored in a database automatic process to find the closest match. Applications include: 1. VIP lists â&#x20AC;&#x201C;make staff aware of important individuals (VIP) and respond in an appropriate manner, 2. Black lists â&#x20AC;&#x201C; identify known offenders or to register suspects to aid public safety, 3. Banking transactions - verification of the persons attempting a financial transaction and so on. Image Acquisition: The image acquisition engine enables you to acquire frames as fast as your camera and PC can support for high speed imaging. Image is captured using digital camera in RGB format. The first function performed by the imaging system is to collect the incoming energy and focus it onto an image plane. Digital and analog circuitry sweeps

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R-image (600nm-700nm)

G-image Camera

(500nm-600nm)

Wavelet

Feature

Transform

R-image

Extraction

(400nm-500nm)

IR-image (1000nm)

Database of Image

Feature Matching

Face ID

Fig.1 Multi-Band Face Recognition Processing

these outputs and Convert them to an analog signal, which is then digitized by another section of the imaging system. The output is a digital image is formed finally. Pre-Processing: Image captured not used for feature Extraction and classification, because captured face Images are affected by various factors such as noise, lighting variance, climatic conditions, poor resolutions of an image, wanted background etc. RGB Image to GRAY Scale Image: RGB images converts to gray scale by eliminating the hue and saturation information while retaining the luminance. Then, add together 30% of the red value, 59% of the green value, and 11% of the blue value. To convert a gray intensity value to RGB, simply set all the three primary color components red, green and blue to the gray value, correcting to a different gamma if necessary. Filtering Techniques: Filtering refers to accepting or rejecting certain frequency components. A filter

ISBN NO : 978 - 1502893314

that passes low frequencies is called a lowpass filter. The Net image produced by lowpass is to blur (smooth) an image. Two Dimensional lowpass

1 if H (u , v)   0 if

D(u , v )  D0 D(u, v)  D0

where D0 is specified nonnegative quantity. A filter that passes high frequencies but reduce amplitude Signal with frequency lower than the sscutoff frequencies.

1 if H (u , v)   0 if

D(u , v )  D0 D(u, v)  D0

where Do is the cutoff distance measured from the origin Of the frequency plane. Wavelets: Wavelets can be used to extract information from many different kinds of data, including – but certainly not limited to – audio signals and images. Sets of wavelets are generally needed to analyze data fully. A set of "complementary" wavelets will decompose data

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without gaps or overlap so that the decomposition process is mathematically reversible.

principal components is less than or equal to the number of original variables.

Wavelet transforms[10] are classified into discrete wavelet transforms (DWTs) and continuous wavelet transforms (CWTs). Both DWT and CWT are continuous-time (analog) transforms. They can be used to represent continuous-time (analog) signals. CWTs operate over every possible scale and translation where as DWTs use a specific subset of scale and translation values or representation grid.

The steps involved in PCA can be summarized as obtain the input matrix; calculate and subtract the mean; calculate the covariance matrix; the Eigenvectors; Eigen values and then forming a new feature vector; once the new feature vector is formed; the new dataset with low dimensions is derived. The new feature vectors are passed to classifier.

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Database Image A continuous wavelet transform (CWT) is used to divide a continuous-time function into wavelets. Unlike Fourier transform, the continuous wavelet transform possesses the ability to construct a timefrequency representation of a signal that offers very good time and frequency localization. A discrete wavelet transform (DWT) is any wavelet transform for which the wavelets are discretely sampled. As with other wavelet transforms, a key advantage it has over Fourier transforms is temporal resolution: it captures both frequency and location information (location in time). Haar Wavelets The first DWT was invented by the Hungarian mathematician AlfrĂŠd Haar. For an input represented by a list of 2 n numbers, the Haar wavelet transform [10] may be considered to simply pair up input values, storing the difference and passing the sum. This process is repeated recursively, pairing up the sums to provide the next n scale: finally resulting in 2 ď&#x20AC; 1 differences and one final sum. B. Feature Extraction: When the input data is too large to be processed then the input data will be transformed into a reduced representation set of features. Transforming the input data into the set of features is called feature extraction. If the features extracted are carefully chosen it is expected that the features set will extract the relevant information from the input data in order to perform the desired task using this reduced representation instead of the full size input. Principal Component Analysis After feature extraction is performed feature vectors are need to minimize. Principal component analysis (PCA)[8] is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. The number of

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To use a standard test data set for researchers to be able to directly compare the results. While there are many databases in use currently, the choice of an appropriate database to be used should be made based on the task given (aging, expressions, lighting etc). Another way is to choose the data set specific to the property to be tested (e.g. how algorithm behaves when given images with lighting changes or images[6] with different facial expressions). If, on the other hand, an algorithm needs to be trained with more images per class (like LDA), Yale face database is probably more appropriate than FERET. Some face data sets often used by researchers: 1.The Color FERET Database, USA: The images were collected in a semi-controlled environment. To maintain a degree of consistency throughout the database, the same physical s etup was used in each photography session. Because the equipment had to be reassembled for each session, there was some minor variation in images collected on different dates. 2. SCface - Surveillance Cameras Face Database: SCface is a database of static images of human faces. Images were taken in uncontrolled indoor environment using five video surveillance cameras of various qualities. 3. Natural Visible and Infrared facial Expression database (USTC-NVIE): The database contains both spontaneous and posed expressions of more than 100 subjects, recorded simultaneously by a visible and an infrared thermal camera, with illumination provided from three different directions. The posed database also includes expression images with and without glasses. C. Feature Matching: If the template image has strong features, a feature-based approach may be considered; the approach may prove further useful if the match in the search image might be transformed in some fashion. Since this approach does not consider the entirety of the template image, it can be more computationally efficient when working with source images of

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larger resolution, as the alternative approach, template-based, may require searching potentially large amounts of points in order to determine the best matching location III. Conclusion Face recognition technology has come a long way for recognising people. Normally the face images are not accurate in single view videos as it does not support pose variations, illumination changes and so on. Hence in order to provide better performance, this work presents the combination of taking Multi -View videos, IR image and Wavelet Transform[10]. Multi -View videos and IR image provides the advantage of overcoming the environmental constraints and providing more accurate image in all conditions when compared with RBG image which provides accurate image only at normal lighting conditions. Wavelet Transform removes redundancies and preserves the originality of the image at multi scales and multiple directions. Thus our approach helps in feature extraction and face matching with high accuracy and less response time. IV. References 1. P. Viola and M. J. Jones, “Robust real-time face detection,” Int. J. Comput.Vis., vol. 57, pp. 137– 154, May 2004. 2. A.C. Sankaranarayanan, A. Veeraraghavan, and R. Chellappa, “Object detection, tracking and recognition for multiple smart cameras,” Proc.IEEE, vol. 96, no. 10, pp. 1606–1624, Oct. 2008. 3.A. Li, S. Shan, and W. Gao, “Coupled biasvariance tradeoff for crosspose face recognition,”

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IEEE Trans. Image Process., vol. 21, no. 1, pp. 305–315, Jan. 2012. 4. A.K. Jain, R. Bolle and S. Pankanti, “Biometrics: Personal Identification in Network Society,” Kluwer Academic Publishers, 1999. 5. V. Blanz and T. Vetter, “Face recognition based on fitting a 3D morphable model,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 25,no. 9, pp. 1063– 1074, Sep. 2003. 6. P. Breuer, K.-I. Kim, W. Kienzle, B. Scholkopf, and V. Blanz, “Automatic 3D face reconstruction from single images or video,” in Proc. IEEE Int. Conf. Autom. Face Gesture Recognit., Sep. 2008, pp. 7. A. Pentland, B. Moghaddam, and T. Starner, “View-based and modular eigenspaces for face recognition,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 1994, pp. 84–91. 8. V. Blanz and T. Vetter, “Face recognition based on fitting a 3D morphable model,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 25,no. 9, pp. 1063– 1074, Sep. 2003. 9. P. Breuer, K.-I. Kim, W. Kienzle, B. Scholkopf, and V. Blanz, “Automatic 3D face reconstruction from single images or video,” in Proc. IEEE Int. Conf. Autom. Face Gesture Recognit., Sep. 2008, pp. 1–8. 10. A. Pentland, B. Moghaddam, and T. Starner, “View-based and modular eigenspaces for face recognition,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 1994, pp. 84–91. 11.Z.Dezhong., C.Fayi, “Face Recognition based on Wavelet Transform and Image Comparison,” International Symposium on Computational Intelligence and Design, 2008.

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A SURVEY ON ONE CLASS CLUSTERING HIERARCHY FOR PERFORMING DATA LINKAGE S.Rajalakshmi, Assistant Professor, Department of CSE, Velammal Engineering College,Anna University, Chennai,India. raji780@yahoo.co.in

Abstractâ&#x20AC;&#x201D; Data linkage refers to the process of matching the data from several databases that refers to the entities of same type. Data linkage is also possible for the entities that do not share the common identifier. With the growing size of the todayâ&#x20AC;&#x2122;s database, the complexity of the matching process becomes a major challenge for Data linkage. Many Indexing techniques were developed for data linkage but however those techniques are not efficient. In this paper, a new data linkage method called as One Class Clustering Tree(OCCT) is developed to overcome the existing challenges and also to perform the data linkage process for the entities that do not share a common identifier. The developed technique builds the tree in such a way that the inner nodes of the tree represents the features of the first set of entities and the leaves of the tree represents the features of the second sets that are similar. The one class clustering tree uses certain splitting criteria and pruning methods for the data linkage. Keywords--Linkage, classification, clustering, splitting, decision tree induction, index techniques.

INTRODUCTION

Data linkage is the process of identifying different entries that refers to the same entity across different data sources[1]. The main aim of the data linkage is to join the datasets that do not share a common identifier or the foreign key. Data linkage is usually performed to reduce the large data into the smaller data. It also helps in removing the duplicate data in the datasets. This technique is called as deduplication [19]. Data linkage can be classified into two types namely, one-to-one data linkage and one-to-many data linkage[15]. In one-to-one data linkage, the aim is to link an entity from one dataset with the matching entity from the other dataset. In one-to-many data linkage the aim is to link an entity from first dat set with the group of matching entities from the other data set. In this paper a new data linkage approach is used called as One Class Clustering Tree(OCCT) which is aimed at performing one-tomany data linkage. The OCCT is most preferable compared to all the indexing techniques because it can easily be translated to linkage rules.

ISBN NO : 978 - 1502893314

A.Jayanthi, M.E(CSE),Department of CSE, Velammal Engineering College,Anna University, Chennai,India. jayanthiarumugamk@gmail.com

The paper is structured as follows: In Section II, we review on indexing techniques,Section III deals with the data linkage using OCCT and finally Section IV concludes the paper. II. INDEXING TECHNIQUES In this section the various indexing techniques are discussed and the variation among them are discussed in more detail. The indexing process of the data linkage can be divided into two phases. 1)Build- All the records in the database are being read and their Blocking Key Values(BKV) are generated. Most of the indexing techniques uses inverted index approach [6] where the record identifiers that have the same BKV will be inserted into the same inverted index list.2)Retrieve- For every block, the list of the record identifiers is retrieved from the inverted index and the candidate record pairs are generated from the list. A.TRADITIONAL BLOCKING Traditional blocking is one of the technique used in the data linkage[1]. In traditional Blocking all the records that have the same BKV are being inserted into the same block and the records within that block are compared with each other. This technique can be implemented using the inverted index[6].The main disadvantage of traditional blocking is that the errors and the variations in the record fields used to generate the BKVs will lead to the record being inserted into the wrong block. The second disadvantage is that the sizes of the block generated depend upon the frequency distribution of the BKVs and thus it is difficult to predict the total number of candidate record pairs that will be generated. B.SORTED NEIGHBORHOOD INDEXING Sorted Neighborhood Indexing helps in sorting the database according to the BKVs,and to subsequently move the window of a fixed number of records over the sorted values and the candidate record pairs are generated only from the records within a current window. It uses three approaches namely sorted array based approach [4],inverted index based

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Proceedings of International Conference on Advancements in Engineering and Technology approach[14] and Adaptive Sorted Neighborhood approach[16].The sorted array based approach is not applicable when the window size is small. However the inverted index based approach also has the same drawback of traditional blocking and it is inefficient approach as it takes lots of time for splitting the entities. The Adaptive sorted Neighborhood approach is not suitable when window size is too large. C. Q-GRAM BASED INDEXING Q-Gram Based Indexing technique overcomes the drawback of the traditional blocking and the sorted neighborhood indexing. The main aim of this technique is to index the database such that the records that have the similar,and not just the same,BKV will be inserted into the same block[8].However, much larger number of candidate record pairs will be generated,leading to a more time consuming process. D. SUFFIX ARRAY-BASED INDEXING Suffix Array-Based Indexing technique is one of the most efficient approach compared to the previous works. The basic idea of this technique is to insert the BKVs and their suffixes into a suffix array based inverted index[11]. It uses the approach called Robust Suffix Array Based Indexing where the inverted index lists of the suffix values that are similar to each other in the sorted suffix array are merged[13]. This technique also takes a lot of time to merge the values.

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III.DATA LINKAGE USING OCCT OCCT is induced using one of the splitting criteria. The splitting criteria is used to determine which attribute should be used in each step of building the tree. OCCT uses the prepruning process to decide which branches should be trimmed.

DATABASE A

DATABASE B

CONSTRUCT OCCT USING ALL ENTITIES

PREPRUNING TECHNIQUE

COMPARE ENTITIES

MATCHING ENTITY

NON-MATCHING ENTITY

E. CANOPY CLUSTERING The canopy clustering[14]is built by converting BKVs into the lists of tokens with each unique token becoming a key in the inverted index. It uses the approach called as the Thresholdbased approach and Nearest Neighbor-Based approach.The drawback of the canopy clustering is similar to that of the sorted neighborhood technique based on the sorted array. F. STRING-MAP-BASED INDEXING String-map-based indexing [9] is based on mapping BKVs to objects in a multidimensional Euclidean Space,such that the distance between the pairs of the strings are preserved.Group of similar strings are then generated by extracting the objects that are similar to each other. However this technique fails when the size of the database is too large or too small. Hence all the above discussed indexing techniques has few drawbacks in the data linkage process. In order to overcome those indexing problems associated with the data linkage process a new approach called as the One Class Clustering Tree is proposed, which uses four splitting criteria namely,Coarse-Grained Jaccard coefficient,Fine-Grained Jaccard Coefficient, Least Probable Intersection(LPI) and Maximum Likelihood Estimation(MLE) for data split and pruning techniques.

ISBN NO : 978 - 1502893314

FINAL RESULT Fig 1: Work Flow Diagram Initially the tree is constructed where the inner nodes of the tree consists of the attribute and the leaves represents the clusters of the clusters of the matching entities. Secondly, the prepruning technique is being used which means that the algorithm stops expanding a branch whenever the subbranch does not improve the accuracy of the model. OCCT uses the probabilistic model to find the similar entities that are to be matched. This probabilistic approach helps to avoid overfitting. OCCT is chosen to be the best approach for data linkage compared to indexing techniques. IV.CONCLUSION In this paper OCCT approach is used which performs one-tomany data linkage.This method is based on the one class decision tree model which sums up the knowledge of which records to be linked together. This method uses one-class approach which gives the results more accurately.OCCT model has also been proved successful in three different domains namely data linkage prevention,recommender system and fraud detection.

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Proceedings of International Conference on Advancements in Engineering and Technology REFERENCES 1.

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I.P. Fellegi and A.B. Sunter, “A Theory for Record Linkage,” J. Am. Statistical Soc., vol. 64, no. 328, pp. 1183-1210, Dec. 1969. D.D. Dorfman and E. Alf, “Maximum-Likelihood Estimation of Parameters of Signal-Detection Theory and Determination of Confidence Intervals—RatingMethod Data,” J. Math. Psychology,vol. 6, no. 3, pp. 487-496, 1969. J.R.Quinlan, “Induction of Decision Trees,” Machine Learning, vol. 1, no. 1, pp. 81-106, March 1986. M.A. Hernandez and S.J. Stolfo, “The Merge/Purge Problem for Large Databases,” Proc. ACM SIGMOD Int’l Conf. Management of Data (SIGMOD ’95), 1995. P.Langley, Elements of Machine Learning, San Franc Isco, Morgan Kaufmann, 1996. I.H. Witten, A. Moffat, and T.C. Bell, Managing Gigabytes, second ed. Morgan Kaufmann, 1999. S.Guha, R.Rastogi and K.Shim, “Rock: A Robust Clustering Algorithm for Categorical Attributes,” Informat- ion Systems, vol. 25, no. 5, pp. 345-366, July 2000. L. Gravano, P.G. Ipeirotis, H.V. Jagadish, N. Koudas, S. Muthukrishnan, and D. Srivastava, “Approximate String Joins in a Database (Almost) for Free,” Proc. 27th Int’l Conf. Very Large Data Bases (VLDB ’01), pp. 491-500, 2001. L. Jin, C. Li, and S. Mehrotra, “Efficient Record Linkage in Large Data Sets,” Proc. Eighth Int’l Conf. Database Systems for Advanced Applications (DASFAA ’03), pp. 137-146, 2003. I.S.Dhillon, S. Mallela, and D.S. Modha, “Information-Theoretic Co-Clustering,” Proc. Ninth ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining, pp. 89-98, 2003. A. Aizawa and K. Oyama, “A Fast Linkage Detection Scheme for Multi-Source Information Integration,” Proc. Int’l Workshop Chal- lenges in Web Information Retrieval and Integration (WIRI ’05), 2005. A.J.Storkey, C.K.I.Williams, E.Taylorand R.G.Mann, “An Expectation Maximisation Algorithm for Oneto- Many Record Linkage,” University of Edinburgh Informatics Research Report, 2005. P. Christen, “A Comparison of Personal Name Matching: Techniques and Practical Issues,” Proc. IEEE Sixth Data Mining Workshop (ICDM ’06), 2006.

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14. P. Christen, “Towards Parameter-Free Blocking for Scalable Record Linkage,” Technical Report TR-CS07-03, Dept. of Com- puter Science, The Australian Nat’l Univ., 2007. 15. P. Christen and K. Goiser, “Quality and Complexity Measures for Data Linkage and Deduplication,” Quality Measures in Data Mining, vol. 43, pp. 127151, 2007. 16. S. Yan, D. Lee, M.Y. Kan, and L.C. Giles, “Adaptive Sorted Neighborhood Methods for Efficient Record Linkage,” Proc. Seventh ACM/IEEE-CS Joint Conf. Digital Libraries (JCDL ’07), 2007. 17. A.Gershman et al., “A Decision Tree Based Recomme- nder System,” in Proc. the 10th Int. Conf. on Innovative Internet Community Services, pp. 170179, 2010. 18. M.Yakout, A.K.Elmagarmid, H.Elmeleegy, M.Quzzani and A.Qi, “Behavior Based Record Linkage,” in Proc. of the VLDB Endowment, vol. 3, no 1-2, pp. 439-448, 2010. 19. P. Christen, “A Survey of Indexing Techniques for Scalable Record Linkage and Deduplication,” IEEE Trans. Knowledge and Data Eng., vol. 24, no. 9, pp. 1537-1555, Sept. 2012, doi:10.1109/TKDE. 2011. 127. 20. M.Dror, A.Shabtai, L.Rokach, Y. Elovici, “OCCT: A One-Class Clustering Tree for Implementing One-toMany Data Linkage,” IEEE Trans. on Knowledge and Data Engineering, TKDE-2011-09-0577, 2013.

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'HQVH 'LHOHFWULF 3DWFK $UUay Antenna- A New Kind of Low-Profile Antenna Element For 5G Cellular Networks B.Praveen Balaji, R.Sriram UG Scholar, Jaya Engineering College, Chennai. praveenbalaji8@gmail.com,sriram3838@gmail.com

ABSTRACT By replacing the metallic patch of a microstrip antenna with a high permittivity thin dielectric slab, a new type of patch antenna, designated as the dense dielectric patch antenna(DD patch antenna),is proposed. At lower microwave frequencies, it has similar performance as the conventional metallic circular microstrip antenna operated in the fundamental TM11 mode. This array antenna is proposed and designed with a standard printed circuit board(PCB) process to be suitable for integration with radio-frequency/microwave circuitary. The proposed structure employs four circular shaped DD patch radiator antenna elements fed by a 1-to-4 Wilkinson power divider surrounded by an electromagnetic bandgap (EBG)structure. The DD patch shows better radiation and total effeciencies compared with the metallic patch radiator. For further gain improvement, a dielectric layer of a superstrate is applied above the array antenna. The calculated impedance bandwidth of proposed array antenna ranges from 27.1 GHz to 29.5 GHz for reflection coeffecient (S11) less than -10dB. The proposed design exhibits good stable radiation patterns over the whole frequency band of interest with a total realized gain more than 16 dBi. Due to the remarkable performance of the proposed array, it can be considered as the best candidate for 5G communication applications.bandgap(EBG)

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Proceedings of International Conference on Advancements in Engineering and Technology

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Advanced mobile signal jammer for GSM, CDMA and 3G Networks with prescheduled time duration using ARM7 TDMI processor based LPC2148 controller 1

Kaku Ramakrishna, Tulasi Sanath Kumar PG Student, Asst. Professor, Department of Electronics & Communication Engineering, ASCET, Gudur, A.P, India

Abstract : This Paper is designed and implemented for mobile phone signal jammers for GSM, CDMA and 3G networks with prescheduled time duration using ARM7.the mobile jammers block mobile phone use by sending out radio waves along the same frequencies that mobile phone use .this case enough interference with the communication between mobile phone and communicating towers to render the phones unusable .upon activating mobile jammers all mobile phones will indicate “NO NETWORK AVAILABLE” . Incoming calls are blocked as if the mobile phone were off. When the mobile jammers are turned off, all mobile phones will automatically re-establish communications and provide full service .the activation and deactivation time schedules can be programmed with microcontroller. Real time clock chip DS1307 is used to set the schedule. In this project we have a jammer section, microcontroller. RTC and GSM modem .this information is given to the microcontroller will send data to GSM just before the select time and GSM will send message to the users whose number are programmed in the GSM that the jammer is going to active and communication will be stopped. After message sent by GSM. Mobile jammer circuit will active and signal are jammed or blocked.

be mentioned that cell phone jammers are illegal devices in most countries. II.

A. Mobile jammer: .a mobile phone jammer is an instrument used to prevent cellular phones from receiver signal from based station. When used, the jammer effectively disables cellular phones. This device can be used in practically any location, but are found primarily in places where a phone call would be particularly in places where a phone call would be particularly disruptive because silence is expected. As with other radio jamming, cell phone jammers block cell phone use by sending out radio waves along the same frequencies that cellular phone use. These causes enough interface with the communication between cell phones and towers to radar the phones unusable. On most retail phones, the network would simply appear out of range. Most cell phones use different bands to send and receive communications from towers (called frequency division depleting, FDD). Jammers can work by either disrupting phone to tower frequencies or tower to phone frequencies. Smaller handheld models block all bands from 800 MHz to 1900 MHz within a 30-foot range (9meters). Small devices tend to used the former method, while larger more expensive models many interfere directly with the tower

Keywords: mobile jammer, ARM7.RTC, GSM modem I.

RELATED WORK

INRODUCTION

Communication jamming device were first developed and used by military. This interest comes from the fundamental objective of denying the successful transport of information from the sender (tactical commander) to the receiver (the army personnel), and vice-versa. Nowadays, mobile phones are becoming essential tool in our daily life. The technology behind cell phone jamming is very simple. The widely use the mobile phone could create some problems as the sound of ringing becomes annoying or disrupting. This could happen in some places like conference room, aw court, libraries, lecture room and mosques.

signals

The jamming device broadcasts an RF signal in the frequency range reserved for cell phones that interference with the cell phone signal, which results in a “no network available” display on the cell phone screen. All phones with in the effective radius of the jammer are science. It should

Base station Figure 1. basic principal mobile signal jammer

1 ISBN NO : 978 - 1502893314

International Association of Engineering and Technology for Skill Development 58

Proceedings of International Conference on Advancements in Engineering and Technology a.

The GSM jammer is a device that transmit signal on the same frequency at which the GSM system operates, the jamming success when the mobile phone in the area where the jammer is located can’t communicate, the basic idea military use that was called denial of service attack. Mobile jammer is used to prevent mobile phone from receiving or transmitting signal with the base stations. When used, the jammer effectively disables cellular phones. There are several ways to jam an RF device. The three most common techniques can be categorized as follows: i.

b. Circuitry: The main electronic components of a jammer are: Voltage-controlled oscillator--generates the radio signal that will interface with the cell phone signal.

In this kind of jamming, the device forces the mobile to turn off itself. This type is very difficult to be implemented since the jamming device first detects any mobile phone in a specific area, then the device sends the signal to disable the mobile phone .some type of this technique can detect if a nearby mobile phone is there and sends a message to tell the user to switch the phone to the silent mode (intelligent beacon disablers).

Tuning circuit – controls the frequency at which the jammer broad cast its signal by sending a particular voltage to the oscillator Noise generator: -- produces random electronic output in a specified frequency range to jam the cell-phone network signal (part of the tuning circuit) RF amplification (gain stage)—boost the power of the radio frequency output to high enough level to jam a signal

Shielding attacks:

This is known as TEMPEST or EMF shielding. This kind required closing an area in a faraday cage so that any device inside this cage cannot transmit or receiver RF signal from outside of the cage. This area can be large as buildings. iii.

Check your phone: -- if the battery on your phone is okay and you’d like to continue your conversation, try walking away from the the area. You may be able to get out of the jammer’s range with just a few steps.

Denial of service

c. Antenna:

This technique is referred to DOS. In this technique, the device transmits a noise signal at the same operating frequency of the mobile phone in order to decrease the signal -to-noise ratio (SNR) of the mobile under its minimum value. This kind of jamming technique is the simplest one since the device is always on. Our device is of this type.

Power supply

IF section

Power supply:

Smaller jamming device are battery operated. Some look like cell-phone batteries. Stronger device can be plugged into a standard outlet or wired in to a vehicle’s electrical system.

Spoofing

ii.

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RF section

Every jamming device has an antenna to send the signal. Some are contained rical cabinet. On stronger device, antennas are external to provide longer range and tuned for individual frequencies. The effect of jamming depends on the jamming-tosignal ratio (j/s), modulation schema, channel coding and interleaving of the target system. Generally jamming-tosignal ratio can measure according to the following equation

Jamming signal

Pj=jammer power,Pt-transmitter power, Gjr=antenna gain from jammer to receiver , Grj=antenna gain from receiver to jammer , Gtr=antenna gain from transmitter to receiver , Grt=antenna gain from receiver to transmitter, Br=communication receiver bandwidth, Bj=jamming transmitter bandwidth, Rtr=rang between communication transmitter and receiver, Rjt=range between jammer and communication receiver, Lr=jammer signal loss, Lr=communication signal loss

Figure2. Block diagram of the jammer device B. Component of mobile jammer: Electronically speaking, cell-phone jammers are very basic device. The simplest just have an on/off and a light that indicates it’s on. More complex device have switches to activate jamming at different frequencies. Components of jammer include:

Jammers simply overflow the frequency used by wireless phones with radio waves. Jamming signal needs enough power to collide and cancel GSM signal. Cell phones are

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D. ARM7TDMI:

designed to increase their power when facing low level interface. Jammer should recognize that power. Power of jamming signal should match the power increase from the phone.

ARM is the abbreviation of advanced RISC machines, it the names of a class of processor, and is the name of kind technology too. The RISC instruction set, and related decode mechanism are much simpler than those of complex instruction set computer (CISC) design. E. Liquid-crystal display (LCD): A flat panel display electronic visual display that uses the light modulation properties of liquid crystal. Liquid crystals do not emit light directly.LCD are available to display arbitrary image or fixed image which can be displayed or hidden, such as preset words, digits, and 7segment displays as in a digital clock. They use the same basic technology, except that arbitrary image is made up of a large number of small pixels, while other displays have large elements.

Sophisticated jammers can block several networks to head off dual or tri-mode phone that automatically switch among different network to find open signal.highend device can block all frequencies.

F. Global system for mobile communication (GSM): GSM/GPRS RS232 modem from rhydoLABZ is built with SIMCOM make sim900 quad-band GSM/GPRS engine .GSM, which stands for global system for mobile communication, reigns (important) as the worldâ&#x20AC;&#x2122;s most widely used cell phone technology. Cell phones use a cell phone service carrierâ&#x20AC;&#x2122;s GSM network by searching for cell phone towers in the nearby area. Global system for mobile communication (GSM) is globally accepted standard for digital cellular communication. GSM is the name of a standardization group established in 1982 to create a common European mobile telephone standard that would formulate specification for a pan-European mobile cellular radio system operating at 900 MHz it is estimated that many countries outside of Europe will join the GSM partnership.

GSM(global system for mobile communication) ranges erope900 MHz, asia-1800 MHz, USA-1.9 MHz C. Micro controller: This section forms the control unit of the whole project. This section basically consists of a microcontroller with its associated circuitry like crystal with capacitors, reset circuit, pull up resistors (if needed) and so on.

Table 1: Operating frequency bands

The microcontroller forms the heart of the project because it controls the drives begins interfaced and communicates with the drives according to the program being written. a microcontroller is a small computer on a single integrated circuit consisting of a relatively simple CPU combined with support function such as crystal oscillator ,timers, watchdog timer, serial and analog i/o etc. microcontroller are also used in specific, high technology, and aerospace projects. Microcontrollers are designed for small or dedicated application.

UPLINK (Handset transmit)

DOWNLINK (handset receive)

USED IN JORDAN BY:

GSM 900

890-915 MHz

935-960MHZ

Zain+orange

DCS 1800

1710-1785 MHz

1805-1880 MHz

Ummiah

In our design, the jamming frequency must be the same the downlink, because it needs lower power to do jamming then the uplink rang and there is no need to jam the base station itself. So, our frequency design will be as follows:

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-- 935-960 MHz

One LCD (liquid crystal display) also interface in this micro controller, it is flat electronic visual display that used that use the light modulating properties of liquid crystals. These components are specialized for being used with the microcontrollers, which means that they cannot be activated by standard IC circuits.

1805-1880 MHz

The CDMA frequency range will be 860-894 MHz (Asia&Europe) and 850-894 MHz (United States). III.

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HARDWEARE IMPLEMENTATION:

RTC (real time clock) is interface because it is widely used device that provides accurate time and date for many applications. LED indicator interface in this microcontroller it have a life of at last ten years and consumer 90 percent less power than conventional indicators, depend on the type of the materials (Ga, AS, p).

The below fig.3 is the block diagram of the system that to set the scheduled time duration for mobile jammer. The activation and deactivation time schedules can be programmed with microcontroller. In order to run the RTC (real time clock) one crystal oscillator is externally interfaced, an oscillator is an electronic circuit that produces a repetitive electronic signal. The power supply interfaced it is used to battery backup for the purpose of update the time when the absence of power. The A.C input i.e., 230v from the mains supply is step down by the transformer to 12v and is fed to a rectifier. One reset button interface, Reset is used for putting the microcontroller into a ‘known’ condition. That partially means that microcontroller can behave rather inaccurately under certain undesirable condition. In order to continuous its proper functioning it has to be reset. Relay is an electrically controllable switch widely used in industrial controls, automobile and appliances.

IV.

LEGAL ISSUES:

India: government and schools use jammers. United States: illegal to operate, manufacture, import, or offer of up to $11,000 and imprisonment of up to one year. Pakistan: legal inside bank, often used also in libraries. United Kingdom: illegal to use, but legal to V.

CONCOLUSION:

This paper is successfully completed using mobile jammer and ARM7.by this system we can deactivate all the mobile signals at any locations. We designed a device that stops phone ringing in particular time period. This device could be used in places where ringing is not desired at specific times, as these ringing may disturb people in such place. The design drive works in dual band. It jams both the GSM900 and GSM1800 bands. The device was able to jam the three main cell phone carriers in Jordan

Power supply

RTC LCD Driver I2C

VI.

LCD

[1] www.howstuffwork.com

ARM7

[2] en.wikipedia.org/wiki/mobile_phone_jammer

LPC2148 GSM modem

Micro controller

REFERENCE

Relay Driver

Relay

[3] multitopic conference2008.INMIC 2008. [4]ccnga.uwaterloo.ca/jscouria/GSM/gsmreporter.html

Jammer circuitry RS232 interface

[5]ieeee explore.com [6]”zone of scilence[cell phone jammer],”spectrum, ieee

Crystal Oscillator

Vol.42,no.5,18,may2005. LED indicators

Reset

Figure: block diagram system

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Artifact Facet Ranking and Itâ&#x20AC;&#x2122;s Application: A Survey Hemalatha.P

Dr.V.Jeyabalaraja

P G Student Department of CSE Velammal Engineering College

Professor Department of CSE Velammal Engineering College

Chennai, Tamilnadu.

Abstract- Various customer surveys of items are currently accessible on the Internet. Customer audits contain rich and significant information for both firms and clients. Be that as it may, the surveys are frequently disordered, prompting challenges in data route and information procurement. This article proposes an item perspective positioning skeleton, which consequently recognizes the essential parts of items from online customer surveys, going for enhancing the ease of use of the various audits. The critical item perspectives are recognized focused around two perceptions: 1) the essential angles are normally remarked on by an extensive number of customers and 2) purchaser suppositions on the essential perspectives significantly impact their general assessments on the item. Specifically, given the customer surveys of an item, we first recognize item angles by a shallow reliance parser and focus buyer suppositions on these angles through a conclusion classifier. We then create a probabilistic perspective positioning calculation to construe the criticalness of perspectives by at the same time considering perspective recurrence and the impact of customer presumptions given to every angle over their general notions. The test comes about on an audit corpus of 21 prevalent items in eight areas show the viability of the proposed methodology. Besides, we apply item viewpoint positioning to two genuine applications, i.e., report level notion characterization and extractive audit synopsis, and accomplish critical execution enhancements, which exhibit the limit of item viewpoint positioning in encouraging certifiable applications.

I INTRODUCTION Late years have seen the quickly growing e-business. A late study from Comscore reports that online retail using arrived at $37.5 billion in Q2 2011 U.S. A huge number of items from different traders have been offered on the web. Case in point, flipkart has listed more than five million items. Amazon.com files a sum of more than 36 million items. Shopper.com records more than five million items from in excess of 3,000 traders. Most retail Websites empowers purchasers to compose surveys to express their conclusions

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on different parts of the items. Here, an angle, additionally called peculiarity in written works, alludes to a part or an characteristic of a certain item. A specimen survey "The battery life of Nokia N70 is astonishing." uncovers positive assumption on the angle "battery life" of item Nokia N70. Other than the retail Websites, numerous discussion Websites additionally give a stage for buyers to post audits on a large number of items. For illustration, Cnet.com includes more than seven million item audits; while Pricegrabber.com contains a large number of audits on more than 33 million items in 25 different classes in excess of 12,000 vendors. Such various shopper audits contain rich and profitable information and have turn into an imperative asset for both shoppers and firms [9]. Buyers usually look for quality data from online audits preceding obtaining an item, while numerous firms use online audits as vital inputs in their item improvement, promoting, and customer relationship administration. By and large, an item may have many perspectives. For instance, iphone 4S has more than three hundred perspectives. We contend that a few perspectives are more essential than the others, and have more prominent effect on the consequent customers' choice making and additionally firms' item advancement techniques. For instance, a few angles of iphone 4S are concerned by most customers, and are more essential than the others for example, "usb" and "catch." For a Polaroid item, the perspectives, for example, "lenses" and "picture quality" would extraordinarily impact customer conclusions on the Polaroid, and they are more essential than the angles, for example, "a/v link" and "wrist strap." Hence, recognizing essential item viewpoints will enhance the ease of use of various surveys and is advantageous to both customers and firms. Shoppers can advantageously settle on astute acquiring choice by paying can concentrate on enhancing the nature of these viewpoints and accordingly improve item notoriety viably. Then again,

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Proceedings of International Conference on Advancements in Engineering and Technology it is unrealistic for individuals to physically recognize the vital parts of items from various surveys. Accordingly, a methodology to naturally recognize the vital angles is profoundly requested. Persuaded by the above perceptions, we in this paper propose an item viewpoint positioning schema to naturally distinguish the vital parts of items from online buyer audits. Our supposition is that the imperative parts of an item have the accompanying qualities: (a) They are regularly remarked in shopper surveys; furthermore (b) Shoppers' assumptions on these perspectives significantly impact their general sentiments on the item. A clear recurrence based result is to respect the viewpoints that are regularly remarked in shopper surveys as paramount. On the other hand, purchasers' suppositions on the regular viewpoints may not impact their general feelings on the item, and would not impact their acquiring choices. For instance, most shoppers often reprimand the awful "sign association" of iphone 4, yet they may in any case give high general evaluations to iphone 4. On the difference, some angles, for example, "plan" and "pace," may not be oftentimes remarked, yet typically are more essential than "sign association." Therefore, the recurrence based result is most certainly not ready to recognize the really critical angles. On the other hand, a fundamental strategy to adventure the impact of purchasers' feelings on particular angles over their general appraisals on the item is to tally the situations where their assessments on particular viewpoints and their general evaluations are predictable, and at that point positions the viewpoints as per the quantity of the predictable cases. This technique basically expects that a general rating was determined from the particular assessments on diverse viewpoints separately, and can't correctly portray the correspondence between the particular assessments and the by and large rating. Subsequently, we go past these strategies and propose a powerful angle positioning methodology to deduce the significance of item viewpoints. As indicated in Fig. 2, given the shopper audits of a specific item, we first recognize viewpoints in the audits by a shallow reliance parser [37] and afterward dissect buyer feelings on these perspectives through an opinion classifier. We then create a probabilistic angle positioning calculation, which adequately abuses the viewpoint recurrence and in addition the impact of buyers' feelings given to every angle over their general sentiments on the item in a brought together probabilistic model. Specifically, we expect the general assessment in a survey is

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created focused around a weighted conglomeration of the assumptions on particular perspectives, where the weights basically measure the level of significance of these angles. A probabilistic relapse calculation is created to derive the essentialness weights by joining angle recurrence and the relationship between the general assessment and the assumptions on particular perspectives. So as to assess the proposed item angle positioning structure, we gather a huge gathering of item audits comprising of 95,660 purchaser surveys on 21 items in eight spaces. These surveys are creeped from different predominant forum websites, for example, Cnet.com, Viewpoints.com, Reevoo.com and Pricegrabber.com and so on. This corpus is avthe impact of customers' conclusions given to each angle over their general sentiments on the item. We show the capability of viewpoint positioning in true applications. Critical execution enhancements are acquired on the applications of record level notion order and extractive survey rundown by making utilization of angle positioning. II ARTIFACT FACET LEVEL AGENDA In this area, we survey the subtle elements of the proposed Item Aspect Ranking schema. We begin with a diagram of its pipeline comprising of three primary segments: (an) angle distinguishing proof; (b) opinion characterization on viewpoints; and (c) probabilistic angle positioning. Given the shopper surveys of an item, we first distinguish the viewpoints in the surveys and after that examine shopper feelings on the angles by means of an opinion classifier. At long last, we propose a probabilistic viewpoint positioning calculation to construe the vitality of the angles by all the while taking into account viewpoint recurrence and the impact of customers' feelings given to every angle over their general sentiments. Let R = {r1, . . . , r|r|} mean a set of buyer surveys of a certain item. In each one audit r â&#x2C6;&#x2C6; R, buyer communicates the notions on different parts of an item, lastly appoints a general rating Or. Alternately is a numerical score that shows diverse levels of general assumption in the audit r, i.e. Then again â&#x2C6;&#x2C6; [omin,omax], where Omin and Omax are the least and greatest appraisals individually. Then again is standardized to [0, 1]. Note that the shopper audits from distinctive Sites may contain different disseminations of appraisals. In general terms, the evaluations on a few Websites may be a little higher or lower than those on others. Additionally, distinctive Sites may offer distinctive rating reach, for instance, the rating reach is from 1 to 5 on Cnet.com and from 1 to 10 on Reevoo.com, individually. Consequently, we here standardize the evaluations from

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Proceedings of International Conference on Advancements in Engineering and Technology distinctive Websites independently, as opposed to performing a uniform standardization on them. This method is relied upon to mitigate the impact of the rating difference among distinctive Websites. Assume there are m perspectives A = {a1, . . . , am} in the survey corpus R absolutely, where ak is the k-th angle. Customer conclusion on angle ak in audit r is indicated as ork. The conclusion on every angle possibly impacts the general rating. We here expect the general rating On the other hand is created focused around a weighted accumulation of the presumptions on particular angle, where each weight Ď&#x2030; r k basically measures the essentialness of angle ak in audit r. We intend to uncover these imperative weights, i.e., the accentuation put on the perspectives, and distinguish the imperative angles correspondingly. In next subsections, we will present the previously stated three segments of the proposed item angle positioning system. It present the item perspective ID that distinguishes perspectives, i.e., {ak}mk =1 in buyer surveys; It will display the perspective level supposition order which examines buyer assessments on perspectives i.e., {ork}|r| r=1; and It will expound the probabilistic perspective positioning calculation that gauges the criticalness weights {Ď&#x2030;rk}|r| r=1 and recognizes comparing essential perspective 2.1 Product Aspect Identification As delineated customer audits are made in distinctive organizations on different gathering Websites. The Websites for example, Cnet.com oblige customers to give a by and large rating on the item, portray compact positive and negative conclusions on some item viewpoints, and in addition compose a section of point by point audit in free content. A few Websites, e.g., Viewpoints.com, request an general rating and a passage of free-content survey. The others for example, Reevoo.com simply require a general rating and some succinct positive and negative assumptions on certain viewpoints. In outline, other than a general rating, a purchaser audit comprises of Pros and Cons surveys, free content survey, then again both. For the Pros and Cons audits, we distinguish the perspectives by removing the continuous thing terms in the audits. Past studies have demonstrated that perspectives are typically things or thing phrases, and we [12] can acquire exceptionally correct perspectives by concentrating successive thing terms from the Pros and Cons audits [19]. For recognizing viewpoints in the free content audits, a clear result is to utilize a current angle recognizable proof methodology. A standout amongst the most striking existing methodology is that proposed by Hu and Liu. It first

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distinguishes the things and thing expressions in the records. The event frequencies of the things and thing expressions are numbered, and just the successive ones are kept as angles. In spite of the fact that this basic strategy is successful sometimes, its well-known constraint is that the distinguished angles typically contain commotions. As of late, Wu et al. [37] utilized an expression reliance parser to concentrate thing expressions, which structure applicant viewpoints. To channel out the commotions, they utilized a dialect demonstrate by an instinct that the more probable an applicant to be an angle, the all the more nearly it identified with the surveys. The dialect model was based on item audits, also used to foresee the related scores of the applicant angles. The hopefuls with low scores were then sifted out. Then again, such dialect model may be predispositioned to the regular terms in the surveys and can't accurately sense the related scores of the angle terms, accordingly can't channel out the commotions successfully. With a specific end goal to get more exact ID of perspectives, we here propose to adventure the Pros also Cons surveys as assistant information to support distinguish angles in the free content surveys. Specifically, we first part the free content surveys into sentences, and parse each one sentence utilizing Stanford parser2. The regular thing expressions are then concentrated from the sentence parsing trees as hopeful perspectives. Since these applicants may contain clam

Fig. 1 .Flowchart of the proposed product aspect ranking framework. [42]

Further power the Pros and Cons audits to aid recognize angles from the hopefuls. We gather all the continuous thing terms extricated from the [23] Pros and Cons audits to structure a vocabulary. We then speak to every angle in the Advantages and disadvantages audits into an unigram offer, and use all the angles to take in an one-class Support Vector Machine (SVM) classifier. The resultant classifier is thus utilized to recognize perspectives in the applicants removed from the free content surveys. As the distinguished angles

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may contain some equivalent word terms, for example, "headphone" and "earphone," we perform equivalent word grouping to acquire special perspectives. In specific, we gather the equivalent word terms of the angles as characteristics. The equivalent word terms are gathered from the equivalent word reference Website3. We speak to every angle into a gimmick vector and utilize the Cosine likeness for grouping. The ISODATA bunching calculation [14] is utilized for equivalent word grouping. ISODATA does not have to settle the number of groups and can gain the number consequently from the information conveyance. It iteratively refines bunching by part what's more uniting of bunches. Groups are blended if the focuses of two groups are closer than a certain edge. One group is part into two separate bunches if the bunch standard deviation surpasses a predefined limit. The qualities of these two edges were experimentally set to 0.2 and 0.4 in our investigations.

A conclusion classifier is then gained from the Pros surveys and Cons audits. The classifier might be SVM, Naïve Bayes or Most extreme Entropy model [23]. Given a free content audit that may blanket various perspectives, we first find the obstinate representation that changes the comparing viewpoint, e.g. finding the representation "well" in the audit "The battery of Nokia N70 works well." for the perspective "battery." Generally, an obstinate representation is connected with the angle on the off chance that it contains no less than one conclusion term in the opinion vocabulary, and it is the closest one to the angle in the parsing tree inside the setting separation of 5. The educated opinion classifier is then leveraged to focus the conclusion of the obstinate representation, i.e. the presumption on the perspective.

2.2 Mawkishness Arrangement on Artifact Facets

In this area, we study a proposed probabilistic viewpoint positioning calculation to distinguish the vital parts of an item from shopper audits. For the most part, vital angles have the accompanying qualities: (a) they are every now and again remarked in shopper audits; and (b) purchasers' feelings on these viewpoints extraordinarily impact their general assessments on the item. The general feeling in an audit is a conglomeration of the feelings given to particular viewpoints in the survey; furthermore different viewpoints have distinctive commitments in the collection. That is, the feelings on (un) important angles have solid (powerless) effects on the era of by and large sentiment. To model such total, we define that the general rating Or in each one audit r is created focused around the weighted aggregate of the suppositions on particular perspectives, as mk =1 ωrkork or in framework structure as ωr Tor. ork is the sentiment on viewpoint ak and the criticalness weight ωrk reflects the accentuation set on ak. Bigger ωrk demonstrates ak is more paramount, furthermore the other way around. ωr signifies a vector of the weights, as well as is the sentiment vector with each one measurement demonstrating the sentiment on a specific facet.

The undertaking of dissecting the assessments communicated on viewpoints is called viewpoint level estimation order in writing. Leaving systems incorporate the administered learning approaches and the vocabulary based methodologies, which are regularly unsupervised. The dictionary based strategies use a feeling dictionary comprising of a rundown of assessment words, expressions and colloquialisms, to focus the estimation introduction on every viewpoint [23]. While these system are effortlessly to execute, their execution depends intensely on the quality of the assumption dictionary. Then again, the managed learning strategies prepare an assessment classifier based on preparing corpus. The classifier is then used to anticipate the assumption on every angle. Numerous learning-based order models are relevant, for instance, Support Vector Machine (SVM), Naive Bayes, and Maximum Entropy (ME) model and so on [25]. Managed learning is subject to the preparing information and can't perform well without sufficient preparing specimens. Nonetheless, marking preparing information is labor-intensive also drawn out. In this work, the Pros and Cons surveys have unequivocally sorted positive and negative assessments on the perspectives. These audits are significant preparing specimens for taking in a supposition classifier. We in this way abuse Pros and Cons audits to prepare a conclusion classifier, which is thus used to focus buyer assessments on the perspectives in free content surveys. Particularly, we first gather the supposition terms in Pros and Cons surveys focused around the notion dictionary gave by MPQA venture [35]. These terms are utilized as peculiarities, and each one survey is spoken to as a gimmick vector.

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2.3 Probabilistic Aspect Ranking Algorithm

III ALLIED WORKS In this area, we audit existing works identified with the proposed item perspective positioning system, and the two assessed genuine applications. We begin with the works on perspective recognizable proof. Existing strategies for perspective recognizable proof incorporate directed and unsupervised systems. Regulated system takes in an extraction model from an accumulation of marked surveys. The extraction show, or called extractor, is utilized to distinguish perspectives in new audits. Most existing

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Proceedings of International Conference on Advancements in Engineering and Technology regulated routines are focused around the consecutive learning procedure [19]. Case in point, Wong and Lam [37] learned viewpoint extractors utilizing Concealed Markรถv Models and Conditional Random Fields, separately. Jin and Ho [11] took in a lexicalized HMM model to separate viewpoints and assessment representations, while Li et al. [16] incorporated two CRF varieties, i.e., Skip-CRF and Tree-CRF. All these strategies oblige sufficient named specimens for preparing. Then again, the time it now, prolonged and work concentrated to name tests. Then again, unsupervised routines have risen as of late. The most outstanding unsupervised methodology was proposed by Hu and Liu. They expected that item perspectives are things and thing expressions. The approach first concentrates things and thing expressions as hopeful perspectives. The event frequencies of the things what's more thing expressions are numbered, and just the incessant ones are kept as perspectives. In this manner, Popescu and Etzioni created the OPINE framework, which removes angles based on the Knowitall Web data extraction framework. Mei et al. used a probabilistic point model to catch the mixture of perspectives and opinions all the while. Su et al. [32] outlined a common fortification technique to at the same time bunch item viewpoints and conclusion words by iteratively intertwining both substance and opinion join data. As of late, Wu et al. [37] used an expression reliance parser to concentrate thing expressions from surveys as perspective hopefuls. They then utilized a dialect model to channel out those impossible perspectives. In the wake of distinguishing angles in surveys, the following errand is viewpoint conclusion order, which decides the introduction of estimation communicated on every perspective. Two major methodologies for perspective slant grouping incorporate dictionary based and managed learning approaches. The vocabulary based routines are normally unsupervised. They depend on a notion dictionary containing a rundown of positive and negative notion words. To create a superb dictionary, the bootstrapping method is generally utilized. Case in point, Hu and Liu [12] began with a set of descriptive word seed words for every conclusion class. They used equivalent word/antonym relations characterized in Wordnet to bootstrap the seed word set, lastly got an assessment vocabulary. Ding et al. introduced a comprehensive dictionary based strategy to enhance Hu's strategy by tending to two issues: the feelings of conclusion words would be substance touchy and clash in the survey. They determined a dictionary by misusing some requirements. Then again, the regulated learning strategies characterize the conclusions on angles by a supposition classifier gained

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from preparing corpus. Numerous learning based models are relevant, for example, Support Vector Machine (SVM), Naive Bayes and Maximum Entropy (ME) model and so forth. More thorough writing audit of angle recognizable proof and estimation characterization might be found in [21]. As previously stated, an item may have hundreds of viewpoints and it is important to recognize the paramount ones. To our best learning, there is no past work contemplating the theme of item perspective positioning. Wang et al. [34] created an inert perspective rating investigation model, which expects to gather analyst's dormant conclusions on every viewpoint and the relative stress on distinctive viewpoints. This work concentrates on angle level assessment estimation and analyst rating conduct dissection, instead of on viewpoint positioning. Snyder and Barzilay [31] formed a various viewpoint positioning issue. Be that as it may, the positioning is really to anticipate the evaluations on individual angles. Record level assessment characterization means to arrange an assumption record as communicating a positive or negative assumption. Existing works use unsupervised, managed or semi-managed learning strategies to manufacture document level assessment classifiers. Unsupervised system as a rule depends on an assessment dictionary containing a gathering of positive and negative assessment words. It decides the general assessment of a survey archive focused around the number of positive and negative terms in the survey. Administered strategy applies existing administered learning models, such as SVM and Maximum entropy (ME) and so on while semi supervised methodology misuses inexhaustible unlabeled surveys together with named surveys to enhance arrangement execution. The other related point is extractive survey outline, which means to consolidate the source surveys into a shorter form saving its data substance and general significance. Extractive outline system structures the outline utilizing the most enlightening sentences and sections and so on chose from the first surveys. The most useful substance by and large alludes to the "most incessant" or the "most positively situated" content in leaving works. The two broadly utilized strategies are the sentence positioning and chart based strategies. In these works, a scoring capacity was initially characterized to process the usefulness of each one sentence. Sentence positioning system [29] positioned the sentences as per their instruction scores and afterward chose the top positioned sentences to structure a rundown. Diagram based technique [7] spoke to the sentences in a diagram, where every hub relates to a

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Proceedings of International Conference on Advancements in Engineering and Technology sentence and each one edge describes the connection between two sentences. An irregular walk was then performed over the diagram t. IV CONCLUSION In this article, we have studies about an item angle positioning structure to recognize the paramount parts of items from various purchaser surveys. The schema contains three principle segments, i.e., item viewpoint recognizable proof, perspective slant characterization, and viewpoint positioning. Initially, we misused the Pros and Cons audits to enhance viewpoint recognizable proof what's more slant characterization on free-content audits. We then created a probabilistic perspective positioning calculation to gather the vitality of different parts of an item from various surveys. The calculation all the while investigates perspective recurrence and the impact of shopper suppositions given to every viewpoint over the general feelings. The item perspectives are at long last positioned as indicated by their essentialness scores. We have directed far reaching investigations to methodicallly assess the proposed schema. The trial corpus contains 94,560 shopper audits of 21 mainstream items in eight areas. This corpus is freely accessible according to popular demand. Test results have showed the adequacy of the proposed methodologies. In addition, we connected item perspective positioning to encourage two true applications, i.e., archive level estimation arrangement and extractive survey synopsis. Noteworthy execution upgrades have been gotten with the assistance of item angle positioning. REFERENCES [1] J. C. Bezdek and R. J. Hathaway, “Convergence of alternating optimization,” J. Neural Parallel Scientific Comput., vol. 11, no. 4, pp. 351–368, 2003. [2] C. C. Chang and C. J. Lin. (2004). Libsvm: A library for support vector machines [Online]. Available: http://www.csie.ntu.edu.tw/∼cjlin/libsvm/ [3] G. Carenini, R. T. Ng, and E. Zwart, “Multi-document summarization of evaluative text,” in Proc. ACL, Sydney, NSW, Australia, 2006, pp. 3–7. [4] China Unicom 100 Customers iPhone User Feedback Report, 2009. [5] ComScore Reports [Online]. Available: http://www.comscore.com/Press_events/Press_releases, 2011. [6] X. Ding, B. Liu, and P. S. Yu, “A holistic lexicon-based approach to opinion mining,” in Proc. WSDM, New York, NY, USA, 2008, pp. 231– 240. [7] G. Erkan and D. R. Radev,“LexRank: Graph-based lexical centrality as salience in text summarization,” J. Artif. Intell. Res., vol. 22, no. 1, pp. 457–479, Jul. 2004. [8] O. Etzioni et al., “Unsupervised named-entity extraction from the web: An experimental study,” J. Artif. Intell., vol. 165, no. 1, pp. 91–134. Jun. 2005. [9] A. Ghose and P. G. Ipeirotis,“Estimating the helpfulness and economic impact of product reviews: Mining text and reviewer characteristics,” IEEE Trans. Knowl. Data Eng., vol. 23, no. 10, pp. 1498–1512. Sept. 2010. [10] V. Gupta and G. S. Lehal, “A survey of text summarization extractive techniques,” J. Emerg. Technol. Web Intell., vol. 2, no. 3, pp. 258–268, 2010.

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[11] W. Jin and H. H. Ho, “A novel lexicalized HMM-based learning framework for web opinion mining,” in Proc. 26th Annu. ICML, Montreal, QC, Canada, 2009, pp. 465–472. [12] M. Hu and B. Liu, “Mining and summarizing customer reviews,” in Proc. SIGKDD, Seattle, WA, USA, 2004, pp. 168–177. [13] K. Jarvelin and J. Kekalainen, “Cumulated gain-based evaluation of IR techniques,” ACM Trans. Inform. Syst., vol. 20, no. 4, pp. 422–446, Oct. 2002. [14] J. R. Jensen, “Thematic information extraction: Image classification,” in Introductory Digit. Image Process., pp. 236–238. [15] K. Lerman, S. Blair-Goldensohn, and R. McDonald, “Sentiment summarization: Evaluating and learning user preferences,” in Proc. 12th Conf. EACL, Athens, Greece, 2009, pp. 514–522. [16] F. Li et al., “Structure-aware review mining and summarization,” in Proc. 23rd Int. Conf. COLING, Beijing, China, 2010, pp. 653–661. [17] C. Y. Lin, “ROUGE: A package for automatic evaluation of summaries,” in Proc. Workshop Text Summarization Branches Out, Barcelona, Spain, 2004, pp. 74–81. [18] B. Liu, M. Hu, and J. Cheng, “Opinion observer: Analyzing and comparing opinions on the web,” in Proc. 14th Int. Conf. WWW, Chiba, Japan, 2005, pp. 342–351. [19] B. Liu, “Sentiment analysis and subjectivity,” in Handbook of Natural Language Processing, New York, NY, USA: Marcel Dekker, Inc., 2009. [20] B. Liu, Sentiment Analysis and Opinion Mining. Mogarn & Claypool Publishers, San Rafael, CA, USA, 2012. [21] L. M. Manevitz and M. Yousef, “One-class SVMs for document classification,” J. Mach. Learn., vol. 2, pp. 139–154, Dec. 2011. [22] Q. Mei, X. Ling, M. Wondra, H. Su, and C. X. Zhai, “Topic sentiment mixture: Modeling facets and opinions in weblogs,” in Proc. 16th Int. Conf. WWW, Banff, AB, Canada, 2007, pp. 171–180. [23] B. Ohana and B. Tierney, “Sentiment classification of reviews using SentiWordNet,” in Proc. IT&T Conf., Dublin, Ireland, 2009. [24] G. Paltoglou and M. Thelwall, “A study of information retrieval weighting schemes for sentiment analysis,” in Proc. 48th Annu. Meeting ACL, Uppsala, Sweden, 2010, pp. 1386–1395. [25] B. Pang, L. Lee, and S. Vaithyanathan, “Thumbs up? Sentiment classification using machine learning techniques,” in Proc. EMNLP, Philadelphia, PA, USA, 2002, pp. 79–86. [26] B. Pang, L. Lee, and S. Vaithyanathan, “A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts techniques,” in Proc. ACL, Barcelona, Spain, 2004, pp. 271–278. [27] B. Pang and L. Lee, “Opinion mining and sentiment analysis,” in Found. Trends Inform. Retrieval, vol. 2, no. 1–2, pp. 1–135, 2008. [28] A. M. Popescu and O. Etzioni, “Extracting product features and opinions from reviews,” in Proc. HLT/EMNLP, Vancouver, BC, Canada, 2005, pp. 339–346. [29] D. Radev, S. Teufel, H. Saggion, and W. Lam, “Evaluation challenges in large-scale multi-document summarization,” in Proc. ACL, Sapporo, Japan, 2003, pp. 375–382. [30] V. Sindhwani and P. Melville, “Document-word co-regularization for semi-supervised sentiment analysis,” in Proc. 8th IEEE ICDM, Pisa, Italy, 2008, pp. 1025–1030. [31] B. Snyder and R. Barzilay, “Multiple aspect ranking using the good grief algorithm,” in Proc. HLT-NAACL, New York, NY, USA, 2007, pp. 300–307. [32] Q. Su et al., “Hidden sentiment association in chinese web opinion mining,” in Proc. 17th Int. Conf. WWW, Beijing, China, 2008, pp. 959– 968. [33] L. Tao, Z. Yi, and V. Sindhwani, “A non-negative matrix trifactorization approach to sentiment classification with lexical prior knowledge,” in Proc. ACL/AFNLP, Singapore, 2009, pp. 244–252. [34] H. Wang, Y. Lu, and C. X. Zhai, “Latent aspect rating analysis on review text data: A rating regression approach,” in Proc. 16th ACM SIGKDD, San Diego, CA, USA, 2010, pp. 168–176. [35] T. Wilson, J. Wiebe, and P. Hoffmann, “Recognizing contextual polarity in phrase-level sentiment analysis,” in Proc. HLT/EMNLP, Vancouver, BC, Canada, 2005, pp. 347–354. [36] T. L. Wong and W. Lam, “Hot item mining and summarization from multiple auction web sites,” in Proc. 5th IEEE ICDM, Washington, DC, USA, 2005, pp. 797–800. [37] Y. Wu, Q. Zhang, X. Huang, and L. Wu, “Phrase dependency parsing for opinion mining,” in Proc. ACL, Singapore, 2009, pp. 1533–1541.

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MOBILE ICU USING ANDROID M. NARMATHA CSE, Final Year Indra Ganesan College Of Engg narmathamano26@gmail.com 9688264699

Mrs. INDRA DEVI (HOD) Dept of CSE Indra Ganesan College Of Engg

G. SIVA RANJANI CSE, Final Year Indra Ganesan College Of Engg sranjani.18@gmail.com 8940184046

ABSTRACT:

Today, though technology is increasing rapidly in one hand, the health issues are also increasing in the other hand. So I proposed a concept to ease hospital work. This work addresses a mini-ICU as it observes all the necessary parameters of the patient that could be employed both in home and hospitals. At the same time, the patient is able to get remote treatment from the doctor which could automatically be stored in the database. This work is found to be more useful at the time of natural disaster where there are numerous patients who need intense care. Also when the patients get back home they might again get infected with that disease so it is used to monitor continuously in their home itself. The main objective of this work is to monitor the patient continuously wherever they are and also to get remote treatment. The main high light is that it is able to work with solar power during power shut downs.

In this Nano world, though technology growing very rapidly to facilitate human life style, but on the other hand health issues are increasing rapidly. Due to current life style, it’s difficult to monitor the dependants if they are not placed together. This leads to continuous monitoring of a person. This makes us to provide a smarter solution to monitor the dependants. In that aspect, we young budding engineers proposed a concept to ease hospital people work and to monitor the person using android mobile”. So I proposed a concept to ease hospital work. This work addresses a mini-ICU as it observes all the necessary parameters of the patient that could be employed both in home and hospitals. At the same time, the patient is able to get remote treatment from the doctor which could automatically be stored in the database.

KEY WORDS: Continuous monitoring, Remote treatment, Android.

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INTRODUCTION:

2. PARAMETERS MEASURED:

The following parameters are measured.      

Heart beat rate Body temperature Coma patient recovery ECG Blood glucose level Saline level monitoring

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BLOCK DIAGRAM

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4.1.1. HEART BEAT SENSOR:

: LCD

PARAMETER

SENSOR

INPUTS

BLUE TOOTH

3.1

ADVANTAGES  Monitors the continuously.

FIG-1: Shows the heart beat sensor

patient

status

 All the necessary parameters are monitored  Remote treatment immediately.  Even coma patient status can be monitored continuously. 

When patients gets well and come back to home from hospital might get infected again, so this is found to be very useful.

 Ability to run with solar power  Applicable for all android mobile. 4.

SYSTEM ARCHITECTURE:

The system architecture consists hardware and software as follows: 4.1.

SYSTEM HARDWARE:

The following hardware.

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describes

the

system

Doctors measure our heart rate manually. We also can feel the pulse on our finger. Our heart does this around 72 to 84 times a minute for a healthy person. But here, we will pass light (using an LED) from one side of the finger and measure the intensity of light received on the other side (using an LDR). Whenever the heart pumps blood more light is absorbed by increased blood cells and we will observe a decrease in the intensity of light received on the LDR. As a result the resistance value of the LDR increases. This variation in resistance is converted into voltage variation using a signal conditioning circuit usually an OPAMP. The signal is amplified enough to be detectable by the microcontroller inputs. The microcontroller can be programmed to receive an interrupt for every pulse detected and count the number of interrupts or pulses in a minute. To save time, only the number of pulses for ten seconds are counted and then multiplied by 6 to get pulse count for 60 seconds/1 minute.

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4.1.2. BODY TEMPERATURE:

4.1.4. ECG:

The LM35 is precision integrated-circuit whose output is linearly proportional to the Celsius temperature. The scale factor is +10.0mv/°c. Hence temperature is equal to Vout*(100°C/V).The voltage from LM 35 is converted to digital format using ADC of ARM controller. This digital value is used to send via SMS after proper conversion.

The system consists of the following subsystems: 1. Patient unit subsystem: This includes electrodes that sense the electrical activity going through the heart, signal amplification circuit, conditioning circuit, data acquisition circuit and home gateway. The circuit takes a reading every 30 minutes and sends it to home gateway PC.

4.1.3. COMA PATIENT RECOVERY: A sensor called Accelerometer that would help to detect any slight movement of an object and the object being in our case is the coma patient who is on bed for a longer duration without any movement. And they are monitored continuously using accelerometer for every time period to detect any tilt made by the patients. Here the transmitter end is fixed on the toe whose movement is received by the receiver end automatically and if there is any movement, this report is sent immediately to the doctor. public class SensorActivity extends Activity, implements SensorEventListener { private final SensorManager mSensorManager; private final Sensor mAccelerometer; public SensorActivity () { MSensorManager= (SensorManager) getSystemService (SENSOR_SERVICE); mAccelerometer = mSenorManager.getDefaultSensor (Sensor._TYPE_ACCELEROMETER); } FIG-2: Shows the java code for accelerometer.

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2. Web Server and Database subsystem: To store the patient ECG signal data, detect any abnormality in the ECG signal and publish the results that can be accessed only by authorized people. 3. Android unit subsystem: Android based application that enables doctors to access the patient details using smart phone.

FIG-3: Patient’s ECG in android mobile. FIG-4: Maximized ECG screen. The ECG signals have Electrode contact noise such as loose contacts, motion artifacts, and baseline drift due to respiration. They also pick electro-magnetic interference caused by other electronic devices surrounding the ECG device and electrodes. Knowing that the standard ECG signal bandwidth ranges between 0.05 Hz and 100 Hz with average amplitude of 1mV

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only, we need to filter the signal with a Low Pass, Band Pass, and a Notch filters. Finally, the resulted signal must be amplified. Next the ECG signals need to be exported to the home gateway. In this project, USB DrDAQ data logger is acquiring the ECG data. It connects to the PC on a USB 2.0 port and to the ECG circuit's output using a probe through the scope channel of the DAQ. The home gateway could be any PC, laptop, iPad, PDA or any other device that can be connected to the Internet. The Home gateway will receive the ECG signal from the data logger and sends it to the healthcare server. 4.1.5 SALINE LEVEL MONITORING: For a patients on bed, there needs someone to monitor the saline level in the bottle else it tends to some risk factors. So here I propose a system that incorporates the LDR that works based on the intensity of light. When the saline water in the bottle is empty it alerts the guide at first and in turn, if he does not notice it, it itself closes the flow with the help of DC motor.

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mobile which can then be sent to the doctor if the condition is critical. 4.2

SYSTEM SOFTWARE:

Hyper Next Android Creator (HAC) is a software development system aimed at beginner programmers that can help them create their own Android apps without knowing Java and the Android SDK. It is based on HyperCard that treated software as a stack of cards with only one card being visible at any one time and so is well suited to mobile phone applications that have only one window visible at a time. Hyper Next Android Creator's main programming language is simply called Hyper Next and is loosely based on Hyper card's Hyper Talk language. Hyper Next is an interpreted English-like language and has many features that allow creation of Android applications. It supports a growing subset of the Android SDK including its own versions of the GUI control types and automatically runs its own. 5.

TESTING RESULTS:

4.1.6 GLUCOMETER: Glucometers use test strips containing glucose oxidase, an enzyme that reacts to glucose in the blood droplet, and an interface to an electrode inside the meter. When the strip is inserted into the meter, the flux of the glucose reaction generates an electrical signal. The glucometer is calibrated so the number appearing in its digital readout corresponds to the strength of the electrical current: The more glucose in the sample, the higher the number which is sent via the blue tooth module to the android

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FIG- 5: Shows the patient details

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SMS sending and SMS receiving programs are working properly are checked on Eclipse software by using AVD manager. The hardware is successfully implemented for remote health monitoring.

CONCLUSION:

In this paper a real-time low cost patient monitoring system is introduced. The developed system produces live parameters that show the analysis of the readings for the abnormalities. If the system detects any of the abnormalities, it will alert the doctor and hospital by sending email and SMS message. The system also implements an application based on Android platform for doctors and for patients. The doctor application provide online information about the patient status, patient history and provides new reading every 30 minutes. This system provides some sort of freedom to both doctor and patient since the results are shown at real-time and the doctor will be alerted on his/her Android device in case of abnormality detection. This system founds to be more helpful at the time of natural calamities where there are numerous patients needing ICU. As a future work, the system can be enhanced more using normal mobiles instead of using android mobiles.

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Electronics and Instrumentation Engineering , Vol. 3, Issue 4, April 2014. [3] Ashokkumar Ramalingam, Prabhu Dorairaj, Saranya Ramamoorthy “ Advanced Health Monitoring and Receiving Using Smartphone in Global Networks”, International Journal on Recent and Innovation Trends in Computing and Communication , Volume: 2 Issue: 6 . [4] Smart Elderly Home Monitoring System with an Android Phone, International Journal of Smart Home Vol. 7, No. 3, May, 2013. [5] Journal of Control and Automation,Vol.2, No.3, September 2009. [6] R. Fensli, E. Gunnarson, and O. Hejlesen, “A Wireless ECG System for Continuous Event Recording and Communication to a Clinical Alarm Station,” 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Francisco, USA; pp 2208-11, 2004 [7] W. Cheng , Y. Ming-Feng., C. KuangChiung, L. Ren-Guey, "Real-time ECG telemonitoring system with mobile phone platform", Measurement, Volume 41, Issue4,pp.463-470,2008.

REFERENCES: [1]Jayalakshmi R, Mahalingam D, Rajeswari A “Personal Safety Triggering System On Android Mobile Platform”, journal of Health & Medical Informatics, Vol4. Issue 2, pp. 1-6, 2013. [2] Ashwini R. Jadhav, Prof. Dr. Virendra V. Shete “Android Based Health Monitoring”, International Journal of Advanced Research in Electrical,

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PURIFICATION OF WATER BY NATURAL ADSORPTION PROCESS K MANOJ KUMAR (R101226),N HEDGERAO(R101811),P SUNIL(R101844),SK IRFAN BASHA (R101883) Dept. of Chemical Engineering, Rajiv Gandhi University of Knowledge Technologies, RK Valley Cuddapah, India -516329

Abstract: Fulfillment of water requirement for flushing and

drinking we implement an natural purification technique to filter out the calcium carbonate, magnesium carbonate and fluorine by using the natural adsorption process, in this paper we take BIO MASS (upper layer of soil),BRICK ASH,SAND as the main raw materials, coming to the process in the first step we will pass the contaminated water along with soil, here it self no changes will occur just soil act as coolant and then from soil to brick ash here florin will be adsorbed by the ash, and in the next stage of the process calcium carbonate and magnesium carbonate particles will be adsorbed by the sand after this one we get the pure water which will be consumable. It is an technique of no maintenance and with low initial cost, including provision of relocate the setup. Reference to this paper should be made as follows: [1] S Chidambaram, AL Ramanathan* and S Vasudevan, (Technical note)-Fluoride removal studies in water using natural materials. [2] Resources and Environment 2013, 3(3): 53-58 DOI: 10.5923/j.re.20130303.02, Sure ndra Roy*, Gurcharan Dass, Fluoride Contamination in Drinking Water – A Review. Nemade, P.D., Kadam, A.M. and Shankar, H.S. (2010) ‘Removal of arsenite from water by soil biotechnology’ ,

INTRODUCION Water is the major medium of fluoride intake by humans. Fluoride in drinking water can be either beneficial or detrimental to health, depending on its concentration. The presence of fluoride in drinking water with in permissible limits is beneficial in the calcification of dental enamel. According to the World Health Organization (WHO), the maximum acceptable concentration of fluoride is 1.5 mg/l, South Africa’s acceptable limit is 0.75 mg /l, while India’s permissible limit of fluoride in drinking water is 1 mg/l. Concentrations beyond these standards have shown dental and skeletal fluorosis, and lesions of the endocrine glands, thyroid and liver. Fluoride stimulates bone formation and small concentrations have beneficial effects on the teeth by hardening the enamel and reducing the incidence of caries. Water treatment provides usable water for domestic agricultural & industrial purposes helps to conserve & enhance water in quality and quantity; in addition prevents degeneration of our water sources of surface & ground. Green technologies today provide impressive water quality at competitive costs without contributing to global warming this technical specification presents a green biological purification engine using a natural adsorption process 1 ISBN NO : 978 - 1502893314

SOURCE AND EFFECT OF FLUORIDE The fluoride -bearing minerals or fluoride-rich minerals in the rocks and soils are the cause of high fluoride content in the groundwater, which is the main source of drinkingwater in India Water is the major medium of fluoride intake by humans. Fluoride in drinking water can be either Beneficial or detrimental to health, depending on its concentration. The presence of fluoride in drinking water within permissible limits is beneficial in the calcification of dental enamel. According to the World Health Organization (WHO), the maximum acceptable concentration of fluoride is 1.5 mg/l, South Africa’s acceptable limit is 0.75 mg/l , while India ’s permissible limit of fluoride in drinking water is 1 mg/l. Concentrations beyond these standards have shown dental and skeletal fluorosis(see the below fig 1 and 2), and lesions of the endocrine glands, thyroid and liver. Fluoride stimulates bone formation and small concentrations have beneficial effects on the teeth by hardening the enamel and reducing the incidence of caries. Mc Donagh et al. Described in great detail the role of fluoride in the prevention of dental fluorosis. At low levels (<2 ppm) soluble fluoride in the drinking water may cause mottled enamel during the formation of the teeth, but at higher levels other toxic effects may be observed. Severe symptoms lead to death when fluoride doses reach 250–450 ppm. It is found that the IQ of the children in the high fluoride areas (drinking water fluoride 3.15 ppm) is significantly low.

Fig: 1 Effect of fluoride on teeth

Fig: 2 Effect of fluoride on bones

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carbonate will adsorbed by sand finally we get consumable cleared water.

Methodology Raw materials Here we are taking the biomass (upper layer of red soil) and

Incinerated Bick ash and sand as our basic raw materials.

Red soil

Contaminated water

Fig. red soil Incinerated brick ash

Sand

Fig. Brick ash

Drinkable water

Rough flow sheet

With Reference to:

Fig. sand Coming to the main process we are passing the contaminated water through first stage in which we use red soil as biomass of coolant here it self no reactions will occur with water, suppose if we passing water at 20 degrees centigrade after coming from soil we will get the water around 18 or 17 degrees centigrade. In second stage we passing the water through the incinerated brick ash here the main adsorption will takes place where the fluoride will adsorbed by the brick ash here we will get a indication like the brick ash will change its color to light yellowish. After that we send water that is come out from brick ash column through grinded rock material - sand here water will repurified after the calcium carbonate and magnesium

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Considerable work on DE fluoridation has been done all over the world. The most economical adsorbent for fluoride removal from drinking water is activated alumina. Borah and Dey has reported other adsorbents like silica gel, soil, bone charcoal, zeolites, betonies, etc which controls the fluoride contamination. They also carried out pilot scale study for the treatment of fluoride using coal particles as adsorbent materials. The amount, contact time and particle size of the adsorbent influenced the treatment efficiencies of fluoride. Concluding Remarks Rock minerals and waste disposal contributes fluoride contamination in groundwater. Researchers have observed different concentrations of fluoride for the different diseases. To mitigate fluoride contamination for an affected area, the provision of safe, low fluoride water from alternative sources should be investigated as the first option otherwise various methods, which have been developed for the DE fluoridation

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of water can be used to prevent fluoride contamination. Groundwater of a particular area should be thoroughly studied before its use for domestic purposes and accordingly a suitable method can be chosen for its treatment. Our process a bio safety and low cost one without using any external energy to give a better solution for contaminated water.

References: [1] WHO, 1984, Environmental Health Criteria for Fluorine and Fluorides., Geneva, 1-136. (2)WHO (World Health Organization), 2006, Guidelines for Drinking-Water Quality: Incorporating First Addendum to Third Edition., World Health Organization, Geneva., 375 p (3)McDonagh, M.S., Whiting, P.F., Wilson, P.M., Sutton, A.J.,Chestnutt, I., Cooper, J., Misso, K., Bradley, M., Treasure, E. and Kleihnen, J., 2000, Systematic review of water fluoridation., Brit. Med. J., 321, 855â&#x20AC;&#x201C;859. (4)Borah, L. and Dey, N.C., 2009, Removal of fluoride from low TDS water using low grade coal., Indian J. Chem. Technol., 16, 361363. (5) Prof. Shankar(iit-b) research topic (6) Meenakshi, R.C., Garg, V.K., Kavita, Renuka and Malik, A., 2004, Groundwater quality in some villages of Haryana, India: focus on fluoride and fluorosis., J. Hazardous Mater., 106, 85-97. (7) Misra, A.K. and Mishra, A., 2007, Study of quaternary aquifers in Ganga Plain, India: Focus on groundwater salinity, fluoride and fluorosis., J. Hazardous Mater., 144, 438-448. (8) Venkateswarulu, P., Rao, D.N., Rao, and K.R., 1952, Studies in endemic fluorosis, Vishakapatnam and suburban areas., Indian J Med Res, 40, 353-62. (9) Meenakshi, R.C. and Maheshwari, 2006, Fluoride in drinking water and its removal., J. Hazardous Mater., 137, 456-463. (10) Yadav, A.K., Kaushik, C.P., Haritash, A.K., Kansal, A. and Rani, N., 2006, Defluoridation of groundwater using brick powder as an adsorbent., J. Hazardous Mater., 128, 289-293. (11) Fluoride Contamination in Drinking Water â&#x20AC;&#x201C; A Review by Surendra Roy , Gurcharan Dass JCDM College of Engineering, Haryana, India

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Secure Data Sharing of Multi-Owner Groups in Cloud 1

Sunilkumar Permkonda , 2D. Madhu Babu

ABSTRACT: Cloud computing provides an economical and efficient solution for sharing group resource among cloud users. Using cloud storage, users can remotely store their data a and enjoy the on-demand high quality application and services from a shared pool of configurable computing resources, without the burden of local data storage and maintenance. However, the fact that users no longer have physical possession of the outsourced data makes the data integrity protection in cloud computing a formidable task, especially for users with constrained computing resources. Sharing data in multi-owner manner while preserving data and identity privacy from an un strusted cloud is still a challenging issues. So, secure cloud authentication system has been proposed, in which users can check the integrity of outsourced data by assigning a third party auditor (TPA) and be worry-free. By using an encryption and hashing technique such as Advanced Encryption Standard (AES),Merkle Hash Tree(MHT) algorithm, any cloud users can anonymously share data with others. Also trustworthiness will be increased between the user and the cloud service provider. KEYWORDS: Cloud computing, data preserving, access control, dynamic groups.

sharing,

privacy-

1. INTRODUCTION Cloud Computing is recognized as an alternative to traditional information technology due to its intrinsic resource sharing and low-maintenance characteristics. In cloud computing ,the cloud service provider(CSPs),such as Amazon, are able to deliver various services to cloud users with the help of powerful datacenters. By migrating the local data management systems into cloud servers, users can enjoy highquality services and save significant investments on their local infrastructures. 1

Sunilkumar Permkonda, M. Tech Student, Department of CSE, JNTUA, Anantapur/ Audisankara Institute of Technology, Gudur /India, (e-mail: sunil55varma@gmail.com). 2

D.Madhu Babu, Assistant Professor Department of CSE, JNTUA/ Anantapur/ Audisankara Institute of Technology, Gudur /India,( e-mail: dmadhubabu@yahoo.com).

One of the most fundamental services offered by cloud providers is data storage. By utilizing the cloud ,the users can be completely released from the troublesome local data storage and maintenance. However, It also poses a significant risk to the confidentiality of those stored files. Specifically, the cloud servers managed by cloud providers are not fully trusted by users while the data files stored in cloud may be sensitive and confidential, such as business plans. To preserve data privacy, as basic solution is to encrypted data files, and then upload the encrypted data into the cloud. Unfortunately. Designing an efficient and secure data sharing schema for groups in the cloud is not an easy task due to the following challenging issues. First, identity privacy is one of the most significant obstacles is one the wide deployment of cloud computing . Without the guarantee of identity privacy, users may be unwilling to join in cloud computing systems because their identities could be easily disclosed to cloud providers and attackers. Second it is highly recommended that any member in a group should be able to fully enjoy the data storing and sharing services provided by the cloud , which is defined as the multi-owner manner. Compared with the single-owner manner, where only the group manager can store and modify data in the cloud , the multiple-owner manner is more flexible in practical applications. More concretely, each user in the group is able to not only read data , but also modify their part of data in the entire data file shared by the company. groups are normally dynamic in practice, e.g., new staff participation and current employee revocation in a company. The changes of membership make secure data sharing extremely difficult. On one hand , the anonymous system challenges new granted users to learn the content of data files stored before their participation, because it is impossible for new ranted users to contact with anonymous data owners, and obtain the corresponding decryption keys. On the other hand, an efficient membership revocation mechanism without updating the secret keys of the remaining users is also desired to minimize the complexity of key management. Several security schemes for data sharing on un trusted servers have been proposed. In these approaches, data

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owners store the encrypted data files in un trusted storage the encrypted and distribute the corresponding decryption keys only to authorizes users. Thus, unauthorized users as well as storage servers can't learn the content of the data files because they have no knowledge of the decryption keys. However the complexities of user participation and revocation in these schemes are linearly increasing with the number of data owner and the number of revoked users, respectively. By setting a group with a single attribute, Lu et al. proposed a secure provenance scheme based on the cipher text-policy attribute-based encryption technique, which allows any member in group to share data with others. However, the issue of user revocation is not addressed in their scheme presented a scalable and fine-grained data access control scheme in cloud computing based o the Key policy attribute-based encryption(KP-ABE) technique. unfortunately, the single owner manner hinders the adoption of their scheme into the case , where any user is ranted to store and share data. 2. RELATED WORKS Several security schemes for data sharing on un trusted servers have been proposed [4], [5], [6]. In these approaches, data owners store the encrypted data files in un trusted storage and distribute the corresponding decryption keys only to authorized users. Thus, unauthorized users as well as storage servers cannot learn the content of the data files because they have no knowledge of the decryption keys. Proposed a cryptographic storage system that enables secure file sharing on un trusted servers, named plutus. By dividing files into file groups and encrypting each file group with a unique file-block key, the data owner can share the file groups with others through delivering the corresponding lockbox key, where the lockbox key is used to encrypt the file-block keys. However, it brings about a heavy key distribution overhead for large-scale file sharing. Additionally, the fileblock key needs to be updated and distributed again for a user revocation. Files stored on the un trusted server include two parts: file metadata and file data. The file metadata implies the access control information including a series of encrypted key blocks, each of which is encrypted under the public key of authorized users. Thus, the size of the file metadata is proportional to the number of authorized users. The user revocation in the scheme is an intractable issue especially for large-scale sharing, since the file metadata needs to be updated. In their extension version, the NNL construction is used for efficient key revocation. However, when a new user joins the group, the private key of each user in an NNL system needs to be recomputed, which may limit the application for dynamic groups. Another concern is that the computation ISBN NO : 978 - 1502893314

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overhead of encryption linearly increases with the sharing scale. Leveraged proxy re-encryptions to secure distributed storage. Specifically, the data owner encrypts blocks of content with unique and symmetric content keys, which are further encrypted under a master public key. For access control, the server uses proxy cryptography to directly re encrypt the appropriate content key(s) from the master public key to a granted user’s public key. Unfortunately, a collusion attack between the un trusted server and any revoked malicious user can e launched, which enables them to learn the decryption keys of all the encrypted blocks. 3.CLOUD COMPUTING SECURITY Cloud Computing Security as “Cloud computing security (sometimes referred to simply as "cloud security") is an evolving sub-domain of computer security, network security, and, more broadly, information security. It refers to a broad set of policies, technologies, and controls deployed to protect data, applications, and the associated infrastructure of cloud computing.” 3.1 Data Security in Existing Cloud Computing System: Cloud Computing is the vast developing technology, but Security is the major challenging issue that is faced by the Cloud Service Providers for handling the Outsourced Data. Although the infrastructures under the cloud are much more powerful and reliable than personal computing devices, they are still facing the broad range of both internal and external threats for data integrity. Thus, Trustworthiness for Data Management system reduced rapidly. To overcome this drawback, there is no big implementation was introduced till now. By using this drawback of the cloud, the hackers are hacking the data from the Cloud Servers. Dynamic broadcast encryption technique is used and users can anonymously share data with others .It allows the data owners to securely share data files with others.

To achieve secure data sharing for dynamic groups in the cloud, we expect to combine the group signature and dynamic broadcast encryption techniques. Specially, the group signature scheme enables users to anonymously use the cloud resources, and the dynamic broadcast encryption technique allows data owners to securely share their data files with others including new joining users. Unfortunately, each user has to compute revocation parameters to protect the confidentiality from the revoked users in the dynamic broadcast encryption scheme, which results in that both the International Association of Engineering and Technology for Skill Development 87

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computation overhead of the encryption and the size of the ciphertext increase with the number of revoked users. Thus, the heavy overhead and large ciphertext size may hinder the adoption of the broadcast encryption scheme to capacitylimited users. To tackle this challenging issue, we let the group manager compute the revocation parameters and make the result public available by migrating them into the cloud. Such a design can significantly reduce the computation overhead of users to encrypt files and the cipher text size. Specially, the computations overhead of users for encryption operations and the cipher text size are constant and independent of the revocation users.

From the above analysis, we can observe that how to securely share data files in a multiple-owner manner for dynamic groups while preserving identity privacy from an un trusted cloud remains to be a challenging issue. In this paper, we propose a novel Mona protocol for secure data sharing in cloud computing. Compared with the existing works, Mona offers unique features as follows: 1.

Any user in the group can store and share data files with others by the cloud.

The encryption complexity and size of cipher texts are independent with the number of revoked users in the system.

User revocation can be achieved without updating the private keys of the remaining users.

A new user can directly decrypt the files stored in the cloud before his participation.

4. PROPOSED CLOUD DATA SECURITY MODEL

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4.1 OVERALL DESIGN: The following figure shows the overall architecture of proposed system.Here the data is stored in a secure manner in cloud and TPA audits the data to verify its integrity. If any part of data is modified or corrupted, then mail alert is sent to the data owner to indicate that the file has been changed.

Figure: System model. 4.2 DATA SECURITY Once Data Owners registers in the cloud, private and public keys are generated for that registered owners. By using these keys, data owners can now store and retrieve data from cloud. A data owner encrypts the data using Advanced Encryption Standard (AES) and this encrypted data is then hashed with Merkle Hash Tree algorithm. By using Merkle Hash Tree algorithm the data will be audited via multiple level of batch auditing process. The top hash value is stored in local database and other hash code files are stored in cloud. Thus the original data cannot be retrieved by anyone from cloud, since the top hash value is not in cloud. Even if any part of data gets hacked, it is of no use to the hacker. Thus, the security can be ensured 4.3DATA INTEGRITY:

To overcome this drawback, we propose secure storage for To check whether the data is modified or not, that is multi-owner data sharing authentication system in loud. If data present in cloud, data owner assigns a third party called owner wants to upload data in cloud, Public and Private Keys Trusted Party Auditor (TPA). Once the data owner sends the will be generated for that user. He first encrypts the data using request to audit the data, TPA checks the integrity of the data Advance Encryption Standard algorithm and then hashes the by getting the hash code files from cloud server and top hash encrypted data using Merkle Hash Tree algorithm. Then the value from db and verifies the file using Merkle Hash Tree data will be given to the Trusted Party Auditor for auditing Algorithm. After each time period, the auditing information purpose. The Auditor audits the data using Merkle Hash Tree will be updated by the Trusted Party Auditor. If any file is Algorithm and stores in the Cloud Service Provider. If the user missing or corrupted, email alert will be sent to data owner wants to View/Download the data, they have to provide the indicating that the data has been modified. The TPA can verify public key. The Data Owners will check the public key the file either by random or in manual way. Thus by allowing entered by the User. If valid, then the decryption key will be the Trusted Party Auditor to audit the data, Trustworthiness provided to the user to encrypt the data. ISBN NO : 978 - 1502893314 International Association of Engineering and Technology for Skill Development 88

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will be increased between the User and Cloud service Providers.

number of group members (i.e., the staffs) as illustrated in Fig. 1.

Our contributions: To solve the challenges presented above, we propose Mona, a secure multi-owner data sharing scheme for dynamic groups in the cloud. The main contributions of this paper include:

Group manager takes charge of system parameters generation, user registration, user revocation, and revealing the real identity of a dispute data owner. In the given example, the group manager is acted by the administrator of the company. Therefore, we assume that the group manager is fully trusted by the other parties. Group members are a set of registered users that will store their private data into the cloud server and share them with others in the group. In our example, the staffs play the role of group members. Note that, the group membership is dynamically changed, due to the staff resignation and new employee participation in the company.

We propose a secure multi-owner data sharing scheme. It implies that any user in the group can securely share data with others by the un trusted cloud.

Our proposed scheme is able to support dynamic groups efficiently. Specifically, new granted users can directly decrypt data files uploaded before their participation without contacting with data owners. User revocation can be easily achieved through a novel revocation list without updating the secret keys of the remaining users. The size and computation overhead of encryption are constant and independent with the number of revoked users.

We provide secure and privacy-preserving access control to users, which guarantees any member in a group to anonymously utilize the cloud resource. Moreover, the real identities of data owners can be revealed by the group manager when disputes occur. We provide rigorous security analysis, and perform extensive simulations to demonstrate the efficiency of our scheme in terms of storage and computation overhead.

4.4 USER AUTHENTICATION:In this module, the user is allowed to access the information from the Cloud Server. When a user registers in cloud, private key and public key will be generated for that user by cloud server. If user wants to view his own file, he uses private key. If user wants to view others file, he uses public key. This public key is split up equally for verification by data owners. Each part of the public key is verified by data owners. After verifying the key, if the key is valid, then user is allowed to access the data. If the key is invalid, then the user is rejected to access the data by Cloud Service Provider. We consider a cloud computing architecture by combining with an example that a company uses a cloud to enable its staffs in the same group or department to share files. The system model consists of three different entities: the cloud, a group manager (i.e., the company manager), and a large ISBN NO : 978 - 1502893314

Cloud is operated by CSPs and provides priced abundant storage services. However, the cloud is not fully trusted by users since the CSPs are very likely to be outside of the cloud users’ trusted domain. Similar to [3], [7], we assume that the cloud server is honest but curious. That is, the cloud server will not maliciously delete or modify user data due to the protection of data auditing schemes [17], [18], but will try to learn the content of the stored data and the identities of cloud users. 4.5 ADVANTAGES  By providing the Public and Private key components, only the valid user will be allowed to access the data.  By allowing the Trusted party Auditorto audit the data, Trustworthiness will be increased between the User and Cloud ServiceProviders.  By using Merkle Hash Tree Algorithm the data will be audited via multiple level of batch auditing Process.  As Business Point of view, the Company’s Customers will be increased due to the Security and Auditing Process. Anonymity and traceability: Anonymity guarantees that group members can access the cloud without revealing the real identity. Although anonymity represents an effective protection for user identity, it also poses a potential inside attack risk to the system. For example, an inside attacker may store and share a mendacious information to derive substantial benefit. Thus, to tackle the inside attack, the group manager should have the ability to reveal the real identities of data owners.

Efficiency: The efficiency is defined as follows: Any group member can store and share data files with others in the group by the cloud . User revocation can be achieved without International Association of Engineering and Technology for Skill Development 89

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involving the remaining users. That is, the remaining users do not need to update their private keys or re-encryption operations. New granted users can learn all the content data files stored before his participation without contacting with the data owner. 5. CONCULSION Data is secured by keeping the top hash value in local database and hash code files in Cloud Server. By enabling TPA to audit he data, integrity is maintained. Authenticating the requested user key by all data owners. we design a secure data sharing scheme, Mona, for dynamic groups in an un trusted cloud. In Mona, a user is able to share data with others in the group without revealing identity privacy to the cloud. Additionally, Mona supports efficient user revocation and new user joining. More specially, efficient user revocation can be achieved through a public revocation list without updating the private keys of the remaining users, and new users can directly decrypt files stored in the cloud before their participation. Moreover, the storage overhead and the encryption computation cost are constant. Extensive analyses show that our proposed scheme satisfies the desired security requirements and guarantees efficiency as well.

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Cloud”, IEEE Trans. On Parallel and Distributed Systems, pp.1182-1191. [8] H. Shacham and B. Waters (2008), “Compact Proofs of Retrievability”, proc. Int’l Conf. Theory and Application of Cryptology and Information Security: Advances in Cryptology (Asiacrypt), pp. 90-107. [9] C. Wang, Q. Wang, K. Ren, and W. Lou (2013), “PrivacyPreserving Public Auditing for Secure Cloud Storage”, IEEE Trans. on Computers, pp. 362-375. [10] S. Yu, C. Wang, K. Ren, and W. Lou (2010), “Achieving Secure, Scalable and Fine Grained Data Access Control in Cloud Computing”, Proc. IEEE INFOCOM, pp. 534 - 542.

6. REFERENCES [1] G. Ateniese, K. Fu, M. Green, and S. Hohenberger (2005), “Improved Proxy Re- Encryption Schemes with Applications to secure Distributed Storage”, Proc. Network and Distributed Systems Security Symp. (NDSS), pp. 29-43 [2] G. Ateniese, R. Burns, R.Curtmola, J. Herring, L. Kissner, Z. Peterson, and D. Song, “Provable Data Possession at Untrusted stores”, proc. 14th ACM Conf. Computer and Comm. Security (CSS ’07), pp. 598-609 [3] K.D. Bowers, A.Juels, and A.Oprea (2009), “HAIL: A High-Availability and Integrity Layer for Cloud Storage”, Proc.ACM Conf. Computer and Comm. Security (CCS ’09), pp. 187-198 [4] A. Fiat and M.Naor (1993),“Broadcast Encryption”, proc. Int’l Cryptology Conf. Advances in Cryptology(CRYPTO), pp.480-491. [5] E.Goh, H. Shacham, N. Modadugu,and D.Boneh (2003), “Sirius: Securing Remote Untrusted Storage”, Proc. Network and Distributed Systems Security Symp. (NDSS), pp. 131145. [6] M.Kallahalla,E.Riedel,R. Swaminathan, Q. Wang, and K. Fu (2003), “Plutus: Scalable Secure File Sharing on Untrusted storage”, Proc.USENIX Conf. File and Storage Technologies, pp. 29-42. [7] X. Liu, Y. Zhang, B. Wang, and J. Yan (2013), “Mona: Secure Multi-Owner Data Sharing for Dynamic Groups in the ISBN NO : 978 - 1502893314

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IMPLEMENTATION OF A WIRELESS SENSOR NETWORK PLATFORM FOR MONITORING TEMPERATURE IN A FOREST AREA K. Thirumala 1, V. Pandu Ranga 2 1

M.Tech Student, Department of ECE, CMR College of Engineering and Technology, Secunderabad Assistant Professor, Department of ECE, CMR College of Engineering and Technology, Secunderabad 1 Mail id: kurimillathirumala12@gmail.com

limiting factor to acquisition accuracy, pervasiveness

ABSTRACT The Wireless sensor networks (WSN) are well suited for continuous environmental data acquisition for

and cost. Two

technologies

were

traditionally

environment temperature representation. This paper presents the functional design and implementation of a complete WSN platform that can be used for a

considered: the radio-frequency identification (RFID) and the wireless sensor networks (WSN).

range of continuous environmental temperature monitoring in a forest area. The application requirements for low cost, high number of sensors,

While the former is well established for low-cost identification and tracking, WSNs bring forest

fast deployment, long life-time, low maintenance, and high quality of service are considered in the specification and design of the platform and of all its

applications richer capabilities for both sensing and actuation. In fact, WSN solutions already

components. Low-effort platform reuse is also considered starting from the specifications and at all design levels for a wide array of related monitoring

cover a very broad range of applications, and research and technology advances continuously

applications. expand their application field. This trend also Index Terms—Wireless Sensor Networks(WSN), Forest

applications,

long

term

environmental

monitoring applications, WSN optimized design,

increases their use in many applications for versatile low-cost data acquisition and actuation.

WSN platform, WSN protocol. However, the sheer diversity of WSN

I.INTRODUCTION

applications makes increasingly difficult to define

More than a decade ago, the parameters of an environment was coined in which computers were able to access data about objects and environment

“typical” requirements for their hardware and software. In fact, the generic WSN components

without human interaction. It was aimed to complement human-entered data that was seen as a

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often need to be adapted to specific application

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requirements and

environmental

conditions.

These ad hoc changes tend to adversely impact

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physical access to the field for deployment and maintenance.

the overall solution complexity, cost, reliability, The generic WSN platforms can be and maintenance that in turn effectively curtail used with good results in a broad class of forest WSN adoption, including their use in forest monitoring

applications.

However,

many

applications. applications (e.g., those in open nature) may To address these issues, the reusable

have stringent requirements, such as very low

WSN platforms receive a growing interest.

cost, large number of nodes, long unattended

These platforms are typically optimized by

service

leveraging knowledge of the target class of

maintenance, which make these generic WSN

applications

platforms less suited.

(e.g.,

domain,

WSN

devices,

time,

ease

deployment,

low

phenomena of interest) to improve key WSN This paper presents the application application

parameters,

such

cost, requirements,

productivity,

reliability,

the

exploration

possible

interoperability, solutions, and the practical realization of a full-

maintenance. custom, reusable WSN platform suitable for use Among the forest application domains,

in low cost long-term environmental monitoring

the environmental/earth monitoring receives a

applications. For a consistent design, the main

growing interest as environmental technology

application requirements for low cost, fast-

becomes a key field of sustainable growth

deployment of large number of sensors, and

worldwide

reliable

environmental

these,

the

monitoring

open is

nature

especially

and

long

unattended

service

are

considered at all design levels. Various trade-

challenging because of, e.g., the typically harsh

offs

between

platform

features

and

operating conditions and difficulty and cost of

specifications are identified, analyzed, and used to guide the design decisions. The development

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methodology presented can be reused for

nature the maintenance can be also very difficult

platform design for other application domains, or

and costly.

evolutions of this platform.

These considerations make the open nature one of the toughest application fields for

Also,

the

platform

requirements

of large scale WSN environmental monitoring, and

flexibility and reusability for a broad range of the Internet of things applications requirements related applications was considered from the for low cost, high service availability and low start. A real-life application, representative for maintenance

further

increase

their

design

this application domain, was selected and used challenges. as reference throughout the design process. To be cost-effective, the sensor nodes Finally, the experimental results show that the often operate on very restricted energy reserves. platform

implementation

satisfies

the Premature energy depletion can severely limit

specifications. the network service and needs to be addressed

II.RELATED WORK

considering the

WSN environmental monitoring includes both indoor and outdoor applications. The later can fall in the city deployment category (e.g., for traffic, lighting, or pollution monitoring) or the open nature category (e.g., chemical hazard, earthquake and flooding detection, volcano and habitat

monitoring,

weather

forecasting,

precision agriculture). The reliability of any outdoor deployment can be challenged by extreme climatic conditions, but for the open

application requirements for

cost, deployment, maintenance, and service availability. These become even more important for monitoring applications in extreme climatic environments, such as glaciers, permafrostâ&#x20AC;&#x2122;s or volcanoes.

The

understanding

such

environments can considerably benefit from continuous

long-term

monitoring,

but

their

conditions emphasize the issues of node energy management, mechanical and communication hardening,

size,

weight,

and

deployment

procedures.

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Open communication

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nature

deployments

and

configuration-free field deployment procedure

protocol

developments

and

suitable for large scale application deployments.

experiments show that WSN optimization for reliable operation is time-consuming and costly. It

hardly

satisfies

the

forest

applications

requirements for long-term, low-cost and reliable service, unless reusable hardware and software platforms

are

available,

including

flexible

Internet-enabled servers to collect and process the field data for environment applications. This paper contributions of interest for researchers

the

WSN

field

can

Fig. 1. Example of an ideal WSN deployment for in situ wildfire detection applications.

summarized as: 1) detailed specifications for a demanding WSN application for long-term

III.ENVIRONMENTAL MONITORING

environmental monitoring that can be used to

REQUIREMENTS

analyze the optimality of novel WSN solutions, 2) specifications, design considerations, and

WSN data acquisition for environmental monitoring applications is challenging, especially for open nature fields. These may require large sensor

experimental results for platform components that suit the typical application requirements of

numbers, low cost, high reliability, and long maintenance-free operation. At the same time, the nodes can be exposed to variable and extreme

low cost, high reliability, and long service time, 3) specifications and design considerations for

climatic conditions, the deployment field may be costly and difficult to reach, and the field devices weight, size, and ruggedness can matter, e.g., if they

platform distributed

reusability

for

event-based

wide

range

are transported in backpacks. Most of these requirements and conditions

environmental

can be found in the well-known application of monitoring applications, and 4) a fast and

wildfire

monitoring

using

situ

distributed

temperature sensors and on-board data processing. In

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its simplest event-driven form, each sensor node

Since these and many related applications

performs periodic measurements of the surrounding

typically use fewer sensor nodes, they are less

air temperature and sends alerts to surveillance

demanding on the communication channels (both in-

personnel if they exceed a threshold. Fig. 1 shows a

field and with the server), and for sensor node energy

typical deployment pattern of the sensor nodes that

and cost. Consequently, the in situ wildfire detection

achieves a good field coverage. For a fast response

application can be used as reference for the design of

time, the coverage of even small areas requires a

aWSN platform

large number

making this

optimized for IoT environmental monitoring and the

application representative for cost, networking and

platform should be easily reusable for a broad class

deployment issues of the event-driven high density

of related applications. Thus, the requirements of

Internet of things application class. In the simplest

aWSN platform for IoT long-term environmental

star topology, the sensor nodes connect directly to the

monitoring can be defined as follows:

gateways, and each gateway autonomously connects

• low-cost, small sensor nodes with on-board

to the server. Ideally, the field deployment procedure

processing,

ensures that each sensor node is received by more

capabilities;

than one gateway to avoid single points of failure of

• low-cost, small gateways (sinks) with self-testing,

the network. This application can be part of all three

error recovery and remote update capabilities, and

WSN categories: event-driven (as we have seen),

supporting

time-driven (e.g., if the sensor nodes periodically

communication;

send the air temperature), and query-driven (e.g., if

• sufficient gateway hardware and software resources

the current temperature can be requested by the

to support specific application needs (e.g., local

operator). This means that the infrastructure that

transducers, and data storage and processing);

supports the operation of this application can be

• detection of field events on-board the gateway to

reused for a wide class of similar long-term

reduce network traffic and energy consumption;

environmental monitoring applications like:

•

• water level for lakes, streams, sewages;

supporting:

• gas concentration in air for cities, laboratories,

—from few sparse to a very large number of nodes;

deposits;

—low data traffic in small packets;

• soil humidity and other characteristics;

• fast and reliable field node deployment procedure;

• inclination for static structures (e.g., bridges, dams);

• remote configuration and update of field nodes;

• position changes for, e.g., land slides;

• high availability of service of field nodes and

• lighting conditions either as part of a combined

servers, reliable data communication and storage at

sensing or

all levels;

standalone, e.g., to detect intrusions in dark places;

• extensible server architecture for easy adaptation to

• infrared radiation for heat (fire) or animal

different IoT application requirements;

sensor

nodes,

field

self-testing,

several

and

types

communication

error

protocol

recovery

long-range

efficiently

detection.

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â&#x20AC;˘ multiple-access channels to server data for both

for the platform nodes, reducing the deployment cost

human

and errors.

operators

and

automated

processing;

programmable multichannel alerts; â&#x20AC;˘ automatic detection and report of WSN platform

IV.WSN NODE DESIGN

faults (e.g., faulty sensor nodes) within hours, up to a day; 3â&#x20AC;&#x201C;10 years of maintenance-free service.

In this section will be presented the use of the specifications defined in Section III to derive the specifications of the WSN platform nodes, design space exploration, analysis of the possible solutions, and most important design decisions.

Fig. 2. Tiered structure of the WSN platform The

gateways

process,

store,

and

A. NODE SECTION DESIGN:

periodically send the field data to the application server using long-range communication channels. The application server provides long-term data storage, and interfaces for data access and process by end users (either human or other applications). The platform should be flexible to allow the

Since forest applications may require large numbers of sensor nodes, their specifications are very important for application performance, e.g., the in situ

distributed wildfire detection selected as

reference for the reusable WSN platform design.

removal of any of its tiers to satisfy specific application needs. For instance, the transducers may me installed on the gateways for stream water level monitoring since the measurement points may be spaced too far apart for the sensor node short-range communications. In the case of seismic reflection geological surveys, for example, the sensor nodes may be required to connect directly to an on-site processing server, bypassing the gateways. And when the gateways can communicate directly with the end user, e.g., by an audible alarm, an application server may not be needed.

the sensor node cost reduction. Also, for low application cost the sensor nodes should have a long, maintenance-free service time and support a simple and reliable deployment procedure. Their physical size and weight is also important, especially if they are transported in backpacks for deployment. Node energy

source

can

influence

several

its

characteristics. Batteries can provide a steady energy flow but limited in time and may require costly maintenance operations for replacement. Energy harvesting sources can provide potentially endless

In addition to the elements described above, the platform can include an installer device to assist the field operators to find a suitable installation place

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One of the most important requirements is

energy but unpredictable in time, which may impact node operation. Also, the requirements of these sources

may

increase

node,

packaging

and

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deployment costs. Considering all these, the battery

on LCD screen and also if the temperature increased

powered nodes may improve application cost and

beyond threshold voltage then it will send the alert

reliability if their energy consumption can be

message to the authorized personâ&#x20AC;&#x2122;s mobile through

satisfied using a small battery that does not require

GSM network.

replacement during node lifetime.

Fig.4: Block diagram of Monitoring Section

V.DEVICE IMPLEMENTATION In the following are presented the most

Fig.3: Block diagram of Node section

important In this node section, Node1 send the reading

platform

implementation devices

that

are

choices based

for

the

of temperature to Node2 then to Node3 then updated in

monitoring

section

Zigbee

wireless

transmission. In monitoring section it will send alert

requirements in Sections III and IV and are suitable for long-term environmental monitoring

messages to the authorized person by using GSM internet of applications.

transmission. Similarly at Node2, it has temperature reading. After some delay it will send to Node3 then to the monitoring section. Then to the authorized person.

A. Sensor Node Implementation: Fig. 3 shows several sensor nodes designed for longterm environmental monitoring applications. The node for in situ wildfire monitoring is optimized for

Similarly at Node3 will send the reading to the monitoring section then to the authorized person

cost since the reference application typically requires a high number of nodes (up to tens of thousands).

through GSM.

B. MONITORING SECTION: The

monitoring

section

receives

the

environmental readings from the nodes and displays

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coordinator implements a priority-based service preemption allowing higher priority service requests to interrupt and take over the gateway control from any lower priority service requests currently being served. This improves the gateway forwarding time of alert messages, for instance. The application tasks implement specific functionalities for the application, such as the message queue, field message handling, sensor node status, field message post processing, RPC, etc. They

Fig.5: (a) firmware structure for reference

are implemented as round-robin scheduled co-

application and (b) operation state flow

routines to spare data memory (to save space and

diagram.

costs the gateway uses only the microcontroller internal RAM). Manual configuration during sensor node deployment

The node microcontroller is an 8 bit

is not necessary because the field node IDs are

ATMEL AT89S52 with 4 KB program and 128 bytes

mapped to the state structure using a memory-

data memory, clocked by its internal 11.0592 MHz

efficient associative array. The node IDs are added as

crystel oscillator (to reduce the costs and energy

they become active in gateway range up to

consumption, since it does not need accurate

1000 sensor nodes and 10 peer gateways, while

timings). The full custom 2 KB program has the

obsolete or old entries are automatically reused when

structure in Fig. 5(a). A minimal operating system

needed.

supports the operation of the main program loop shown in Fig. 5(b) and provides the necessary interface with the node hardware, support for node self-tests, and the communication protocol.

B. Gateway Node Implementation: Fig. 6 shows the layers of the full custom software structure of the gateway. The top-level operation is controlled by an application coordinator. On the one hand, it accepts service requests from various gateway tasks (e.g., as reaction to internal or external events, such as message queue nearly full or alert

message

received

from

field

sensors,

Fig.6: Gateway firmware block diagram. In

fact,

gateways

deployed

inside

respectively).On the other hand, the coordinator triggers the execution of the tasks needed to satisfy the service request currently served. Also, the

ISBN NO : 978 - 1502893314

sewages

for

level

monitoring

applications

receiving data from one sensor node and no

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peers operate for one year on 19 Ah batteries,

field

which

theoretical

communication segments, with latency-energy

calculations above. It is also worth noting that

trade-offs, and the fast and ubiquitous end user

the gateway average current can be further

field

reduced by using the hardware SPI port to

applications). The full custom server software

interface

has the structure shown in Fig. 8. It provides

consistent

with

the

with

radio

the

devices

and

data.

data

www.iaetsd.in

bridges

access

(by

the

low

humans

power

IoT

programming the latter to autonomously scan for

interfaces for:

incoming packets instead of the software-

• field nodes (gateways);

controlled LPL over a software SPI port

• the operators and supervisors for each field;

emulation used currently.

• various alert channels; • external access for other IoT systems. Each interface has a processing unit that includes, e.g., the protocol drivers. A central engine controls the server operation and the access to the main database. It is written in Java, uses a MySQL database and runs on a

Fig.7: Block structure of the deployment

Linux operating system. Two protocols are used to interface with the field nodes (gateways) for

device. an

energy-efficient

communication

over

The repeater node uses the gateway unreliable connections: normal and service (boot design with unused hardware and software loader) operation. The normal operation protocol components removed. acknowledges each event upon reception for an

VI. APPLICATION SERVER incremental release of gateway memory The main purpose of a WSN application server is to receive, store, and provide access to

ISBN NO : 978 - 1502893314

even

for

prematurely

interrupted

communications. Messages and acknowledges

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can be sent asynchronously to improve the

its lifetime. For example, Fig. 12 shows some

utilization

typical deployments for the reference application

high

latency

communication

channels.

nodes. Node deployment can be a complex,

Time

time-consuming, error-prone, and manpower-

avoided at every communication level. The

intensive operation, especially for applications

gateways timestamp the field messages and

with a large number of nodes. Thus, it needs to

events using their relative time and the server

be guided by automatic checks, to provide quick

converts it to real-world time using an offset

and easy to understand feedback to field

calculated

gateway

operators, and to avoid deployment-time sensor

communication session. The protocol for the

or gateway node configuration. The check of

boot loader mode is stateless, optimized for

node connectivity with the network is important

large data block transfers and does not use

for star topologies and especially for transmit-

acknowledges. The gateway maintains the

only nodes (like the reference application sensor

transfer state and incrementally checks and

nodes). These nodes cannot use alternative

builds the firmware image. An interrupted

message routing if the direct link with the

transfer can also be resumed with minimal

gatewayis lost or becomes unstable.

synchronization

the

begin

overhead

the

overhead.

The

deployment

procedure

the

sensor node of the reusable WSN platform takes

VII. FIELD DEPLOYMENT

into account the unidirectional communication capabilities of the sensor nodes. It is also

PROCEDURE designed to avoid user input and deploymentThe node deployment procedure of the time configurations on the one hand, and a fast WSN platform aims to install each node in a field automatic

assessment

the

deployment

location both close to the application-defined position and reliable concurrent neighbor node position and that ensures a good operation over deployment on the

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other hand. The sensor nodes are temporarily

deployment state, (b) display position suitability.

switched to deployment operation by activating

The deployment device collects all the data, and

their on-board REED switch using a permanent

computes and

magnet in the deployment device, as shown in

displays an assessment of deployment position

Fig.8(a). This one-bit near field communication

suitability. No gateway or node configuration is

(NFC) ensures a fast, reliable, input-free node

required and the procedure can be repeated

selectivity. Its device ID is collected by the

until a suitable deployment position is found.

deployment device that listens only for strong deployment messages. These correspond to nodes within just a few meters providing an

VIII.RESULTS effective insulation from collecting IDs of nearby Power supply circuit schematic: concurrent node deployments. The gateways that receive the sensor node deployment messages report the link quality with the node [see Fig. 8(b)].

Node section schematic:

Fig.8: Field deployment of sensor nodes: (a) use deployment device magnet to set to deployment state, (b) display position suitability.

Field deployment of sensor nodes: (a)

Monitoring Section Schematic:

use deployment device magnet to set to

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IX. CONCLUSION In proposed method power consumption will be reduced.

Long range

communication

will

provided. The security is high. The application requirements for low cost, high number of sensors, fast deployment, long lifetime, low maintenance, and high quality of service are considered in the specification and design of the WSN platform and of all its components.

REFERENCES [1] K. Romer and F. Mattern, “The design space of wireless sensor networks,” IEEE Wireless Commun., vol. 11, no. 6, pp. 54–61, Dec. 2004. [2] I. Talzi, A. Hasler, S. Gruber, and C. Tschudin, “Permasense: Investigating permafrost with a WSN in the Swiss Alps,” in Proc. 4th Workshop Embedded Netw. Sensors, New York, 2007, pp. 8–12. [3] P. Harrop and R. Das,Wireless sensor networks 2010–2020, IDTechEx Ltd, Cambridge, U.K., 2010. [4] N. Burri, P. von Rickenbach, and R. Wattenhofer, “Dozer: Ultra-low power data gathering in sensor

ISBN NO : 978 - 1502893314

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networks,” in Inf. Process. Sensor Netw., Apr. 2007, pp. 450–459. [5] I. Dietrich and F. Dressler, “On the lifetime of wireless sensor networks,” ACM Trans. Senor Netw., vol. 5, no. 1, pp. 5:1–5:39, Feb. 2009. [6] B. Yahya and J. Ben-Othman, “Towards a classification of energy aware MAC protocols for wireless sensor networks,” Wireless Commun. Mobile Comput., vol. 9, no. 12, pp. 1572–1607, 2009. [7] J. Yang and X. Li, “Design and implementation of low-power wireless sensor networks for environmental monitoring,” Wireless Commun., Netw. Inf. Security, pp. 593–597, Jun. 2010. [8] K. Martinez, P. Padhy, A. Elsaify, G. Zou, A. Riddoch, J. Hart, and H. Ong, “Deploying a sensor network in an extreme environment,” Sensor Netw., Ubiquitous, Trustworthy Comput., vol. 1, pp. 8–8, Jun. 2006. [9] A. Hasler, I. Talzi, C. Tschudin, and S. Gruber, “Wireless sensor networks in permafrost research— Concept, requirements, implementation and challenges,” in Proc. 9th Int. Conf. Permafrost, Jun. 2008, vol. 1, pp. 669–674. [10] J. Beutel, S. Gruber, A. Hasler, R. Lim, A. Meier, C. Plessl, I. Talzi, L. Thiele, C. Tschudin, M. Woehrle, and M. Yuecel, “PermaDAQ: A scientific instrument for precision sensing and data recovery in environmental extremes,” in Inf. Process. Sensor Netw., Apr. 2009, pp. 265–276. [11] G. Werner-Allen, K. Lorincz, J. Johnson, J. Lees, and M. Welsh, “Fidelity and yield in a volcano

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monitoring sensor network,” in Proc. 7th Symp. Operat. Syst. Design Implement., Berkeley, CA, 2006, pp. 381–396. [12] G. Barrenetxea, F. Ingelrest, G. Schaefer, and M. Vetterli, “The hitchhiker’s guide to successful wireless sensor network deployments,” in Proc. 6th ACM Conf. Embedded Netw. Sensor Syst., New York, 2008, pp. 43–56.

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