Advance Database and Management vol 3 issue 3 by STM Journals

ISSN 2393-8730 (Online)

Journal of Advanced Database Management & Systems (JoADMS) Septemberâ&#x20AC;&#x201C;December 2016

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Journal of Advanced Database Management & Systems ISSN: 2393-8730 (online)

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It is my privilege to present the print version of the [Volume 3 Issue 3] of our Journal of Advanced Database Management & Systems, 2016. The intension of JoADMS is to create an atmosphere that stimulates vision, research and growth in the area of Data Base Management & System. Timely publication, honest communication, comprehensive editing and trust with authors and readers have been the hallmark of our journals. STM Journals provide a platform for scholarly research articles to be published in journals of international standards. STM journals strive to publish quality paper in record time, making it a leader in service and business offerings. The aim and scope of STM Journals is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high level learning, teaching and research in all the Scientific, Technical and Medical domains. Finally, I express my sincere gratitude to our Editorial/ Reviewer board, Authors and publication team for their continued support and invaluable contributions and suggestions in the form of authoring writeups/reviewing and providing constructive comments for the advancement of the journals. With regards to their due continuous support and co-operation, we have been able to publish quality Research/Reviews findings for our customers base. I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.

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Journal of Advanced Database Management & Systems

Contents

1. A Review on Big Data Divya Chauhan, K.L. Bansal

2. Effective Implementation of Apriori Algorithm to Develop a Suggestion System Based on Sales History Using Hadoop Environment Aishwarya Rani M.R., Shivanand R.D.

3. IoT Based Biometric System K.P. Swain, M.V.S.V. Prasad, J. Sahoo, S. Sharma, G. Palai

4. A Review on Inventory Management System for Improving Efficiency of Project Development Cycle Sagar S. Mehta, Prasad S. Puranik, Satish B. Sharma

5. Information Privacy and Security in Data Mining Likhitha A.R., Vandana B.S., Savitha C.K., Ujwal U.J.

Journal of Advanced Database Management & Systems ISSN: 2393-8730(online) Volume 3, Issue 3 www.stmjournals.com

A Review on Big Data Divya Chauhan*, K.L. Bansal Department of Computer Science, Himachal Pradesh University, Shimla, Himachal Pradesh, India Abstract The goal of Big Data is to help organizations make better business decisions based on information by enabling researchers, data scientists and other analytics professionals to analyze large volumes of operational data, as well as other forms of data that may not be discovered by conventional Business Intelligence (BI) programs. This gives rise to the need for an analytical review of recent developments in the big data technology. Cloud services were used to process huge amount of data and it has turned into new Big Data model to meet the on demand services. This paper aims to provide a comprehensive review of big data applications and challenges, which it is facing. In addition to that, several research areas have been highlighted for future directions. The survey will be beneficial for the further enhancement and enrichment of Big Data Analytics in various research perspectives. Keywords: Big Data, Hadoop, Big Data Analytics

INTRODUCTION Businesses have always struggled long to find an optimized approach for capturing information about their customers, services and products. Managing and analyzing data for organizations have always offered the greatest benefits and the greatest challenges across all industries. But with the advent in time, the market with which they worked has grown with the time. Previously there used to be few customers, the information about them was straightforward and easy to handle. It is not only the plight of business, the research and development (R&D) organizations have struggled to get enough computing power to run sophisticated models or to process images or other sources of scientific data. When there is so much information, that too in so many different forms, it is difficult to deal with it with the traditional data management ways. Working in the era of enormous data, Big Data is important because it enables organizations to store, manage, gather, and manipulate vast amounts data at the right time, at the right speed, to gain the right insights. Big Data is the result of last 50 years of technology evolution. It is not a stand-alone technology. The Big Data is nothing but a data, available at heterogeneous, autonomous sources, in extremely large amount, which are updated in fractions of seconds [1]. The next section describes the waves or journey of the data. Subsequent sections give the overview of five

Vâ&#x20AC;&#x2122;s of Big Data and discuss the technical changes being faced by Big Data. Later in the paper, applications of Big Data are also discussed. A separate section highlights the research area and recent evolvement in Big Data and last section gives the conclusion.

THE WAVES OF MANAGING DATA The revolution in the data from generations has been classified into three waves, where each wave describes the journey of the data and techniques evolved to handle it [2]. Wave1: Creating Manageable Data Structures Initially data used to be stored in files. To give it a level of abstraction, RDBMS was incarnated to give programmers ease in extracting values from data to satisfy the growing needs of the business. But the data volume kept growing. So the data were fragmented and distributed over different locations. But this added duplication and redundancy to the data. At this stage, an urgent need was felt to find a new set of technologies to support the relational model. Entity relationship models served the purpose by adding additional abstraction to increase the usability of the data. Data warehouse also played there part when data grew out of control. But with time, data warehouse grew too complex and large and did not provide the speed and agility that the businesses were expecting. So there was further refinement of

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Journal of Advanced Database Management & Systems ISSN: 2393-8730(online) Volume 3, Issue 3 www.stmjournals.com

Effective Implementation of Apriori Algorithm to Develop a Suggestion System Based on Sales History Using Hadoop Environment Aishwarya Rani M.R.*, Shivanand R.D.2 Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davanagere, Karnataka, India

Abstract The need for comprehensive support system to analyze and predict the nature of the dynamic market based on the previous records is very vital in competent industries today. The data mining is a process of extracting implicit, previously unknown and potentially useful information from data. Mining is search for relationships and global patterns that exist in the large databases but that are hidden among vast amount of data. Since the data collected tends to be huge and complex, it is necessary to structure it and process it using evolving technologies like Hadoop. Apriori algorithm is an algorithm for frequent itemsets mining and association rule learning over transactional database. This algorithm helps in finding out the frequent itemsets and thus deriving the association rule between the itemsets. Apriori algorithm when used in Hadoop framework is proven to be highly effective, with regard to time complexity. A MapReduce framework is a major part of Hadoop and performs filtering and sorting and a summary operation. This paper aims at providing solution to the task of analyzing the sales and distribution function of an enterprise using the latest Hadoop technology. Keywords: A priori algorithm, data mining, frequent itemsets, association rules, Hadoop MapReduce

INTRODUCTION Big data means data sets whose volume is very large and of wide variety, some commonly used software tools are not able enough to manage data. Data mining is a process of identifying valid, novel, potentially useful and ultimately understandable patterns in data. Apriori algorithm is one of the data mining algorithms for frequent itemset mining and association rule learning over transactional database [1]. It helps in finding out the frequent itemsets from a given data repository and thus deriving the association rules between the itemsets. The key idea of Apriori algorithm is to make multiple passes over the database. The working of Apriori algorithm fairly depends upon the Apriori property which states that “All nonempty subsets of a frequent itemsets must be frequent”. The main objective of the proposed work is to reduce the response time of Apriori algorithm and to speed-up the algorithm. Thus, in order to find the frequent itemsets, there is a need to scan

the database again and again. The main limitation of Apriori algorithm is costly wasting of time to hold a vast number of candidate sets. In addition, single processor’s memory and CPU resources are very limited, which make the algorithm performance inefficient. Furthermore, because of growth of information, enterprises have to deal with growing amount of data. So, the solution to this problem is parallel and distributed computing. This can be achieved by Hadoop Map-Reduce model. Hadoop is an open source framework for processing and storing large datasets over a cluster and it is used in handling large and complex data which may be structured, unstructured or semi-structured [2]. Hadoop distributed file system (HDFS) is a distributed file system, which rests on top of the native file system and is written in java. It is highly fault tolerant and is designed for commodity hardware. HDFS has a high

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Journal of Advanced Database Management & Systems ISSN: 2393-8730(online) Volume 3, Issue 3 www.stmjournals.com

IoT Based Biometric System K.P. Swain1,*, M.V.S.V. Prasad2, J. Sahoo2, S. Sharma3, G. Palai1 1

Department of Electronics and Communication Engineering, Gandhi Institute for Technological Advancement, Bhubaneswar, Odisha, India 2 Department of Electrical and Electronics Engineering, Gandhi Institute for Technological Advancement, Bhubaneswar, Odisha, India 3 Deptartment of Computer Science and Engineering, International Institute of Information Technology, Bhubaneswar, Odisha, India

Abstract Research on “Internet of Things” (IoT) is burgeoning time to time owing to its real application in the field of science and technology. The combination of cloud computing, big data, future internet, robotics, semantic technologies, and IoT deal with several applications in every automation pitch. IoT integrates the real world data and services into current information networking for realizing different practical devices. In view of importance of Internet of Things, this paper design and implement, the cloud-based biometric attendance system using a low-cost IoT device Raspberry Pi. Present work has many advantages like desktop notification about the individual attendance info to the concerned person and checking own database by using both web and Android App from anywhere in the globe. Keywords: IoT, Raspberry Pi, biometric, real-time

INTRODUCTION Biometric authentication, most often termed as simply biometrics is used to verify the identity of a living person depending upon some physiological parameters, despite the entire cross individual similarities [1]. It is always used with some computational devices, which give more accurate result in many real-time applications like ATM, Aadhar Cards, voting machine, security systems, attendance systems, etc. Internet of Things (IoT) was first described by Kevin Ashton, a British scientist in 1999 where the physical object is connected to the Internet by using sensors [2]. He illustrated how RFID can be used in a supply chain system to count and track goods by the help of the internet which drastically reduce the human intervention. Afterwards, Internet of Things turns out to be gigantic widespread in automatic system by significantly reducing the manpower. At present, IoT acquired a very lucrative trend by the combination of cloud computing and the low cost device like Raspberry Pi, Arduino, Edison.

In this work, a Raspberry Pi 2 board is used along with a fingerprint sensor and a touch screen LCD is used to log daily attendance for an educational organization. Here, Raspberry Pi 2 board us acts a Linux based minicomputer used to store individual information in its database and synchronize with remote database.

RELATED WORK In the investigations [3, 4], Raspberry Pi is efficiently used as an authentication node in a cloud based biometric system for remote enrolment. A Raspberry Pi along with Arduino, Xbee and relay modules used in smart drip irrigation system where user command is processed at Raspberry Pi using python language [5]. By using Zigbee protocol, on/off command is received by Arduino microcontroller from Raspberry Pi. Between Raspberry Pi and end user communication star topology is used. A wireless sensor network system is developed using Raspberry Pi and Zigbee, which can be used for variety of environment monitoring application [6]. Also, in this Raspberry Pi is used a base station to collect different sensors

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Journal of Advanced Database Management & Systems ISSN: 2393-8730(online) Volume 3, Issue 3 www.stmjournals.com

A Review on Inventory Management System for Improving Efficiency of Project Development Cycle Sagar S. Mehta1,*, Prasad S. Puranik1, Satish B. Sharma2 1

Department of Mechanical Engineering, Atmiya Institute of Technology and Science Rajkot, Gujarat, India 2 Space Application Centre, Indian Space Research Organization, Ahmedabad, Gujarat, India

Abstract Inventory is a major element of many organizations. Consequently, its proper control is crucial for the profitability of the organization and development of circumventing communities. Inventory Management System (IMS) enables the visualization, specification, and documentation of a software-intensive system. The software was tested for enhancing the workflow and providing a timely and efficient handling. The manual system requires everyday counting of items in the inventory, human errors are very prevalent during counting and recording and all the manual inventory records will be damaged and irretrievable. In light of the discoveries this paper highlights the possible solutions to the above quandaries; a computerized IMS to issue and update the stocks. Keywords: Inventory Management System, Project Development Life Cycle

INTRODUCTION Inventory Management System (IMS) provides a flexible and easily understood way of analyzing complicated problems. The method has been used in several areas including performance evaluation, project management, inventory management, resource allocation, budgeting decisions, etc. Low inventory may lead to stock outs, which result in production halts, inability to meet deadlines, customer dissatisfaction and loss of goodwill. On the other hand, high inventory levels block huge capital, which is a scarce resource for any organization. For organizations that maintain thousands of inventory items, it is unrealistic to provide equal consideration to each item. Inventory is one of the largest and most important assets of a manufacturing business. The main purpose of the inventory management practices in all production companies is to have the required items ready to be processed right on the required time with incurring minimum cost. The need of inventory IMS emerges from the way that

manual taking care of may bring about human blunders, which may influence the inventory utilization. With a specific end goal to robotize the procedure, a thorough study on the system should be conducted. The essential objective of Inventory Administration System is to give a documentation that is effortlessly comprehended by all clients inside the association. IMS plays an important role for a successful enterprise. With a correct framework, it is easier to provide coordination between units, eliminate waste, and make faster and better decisions. It is intended to those organizations that need to receive and ship goods, while keeping up an ideal use of space and knowing particularly where all products are put away at any given time. IMS enhances real-time data capture, and the automation of warehouse. The common warehouse tasks can all be optimized to save time to make for greater profits. Inventory management is the process of productively

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Journal of Advanced Database Management & Systems ISSN: 2393-8730(online) Volume 3, Issue 3 www.stmjournals.com

Information Privacy and Security in Data Mining Likhitha A.R.*, Vandana B.S., Savitha C.K., Ujwal U.J. Department of Computer Science, KVG College of Engineering, Sullia, Karnataka, India

Abstract The improving popularity and growing of data mining technologies bring very serious effect to the security of individual's sensitive information. In the recent years, the privacy preserving data mining (PPDM), has been extensively studied and it is an emerging research subject in data mining. Without accommodating the security of sensitive information contained in the data, the basic idea of PPDM is to implement the data in such a manner so as to execute data mining algorithms effectively. While in fact, data collecting, data publishing, and information delivering happen only in the process of unwanted disclosure of sensitive information. Here, the privacy issues equal to the data mining from a wider perspective and investigate many different approaches which can help to save or protect the sensitive information. In data mining, there are four different types of users involved, namely data provider, data collector, data miner and decision maker. The four types of users, which discuss user privacy and concerns the methods that can adopted to protect sensitive information. The basics of parallel research topics, evaluate state-of-the-art approaches existing, some preliminary thoughts on upcoming research directions are introduced briefly here. Each type of user exploring the privacy-preserving approaches; and also find the game theoretical approaches. In data mining scenario, the approaches are proposed for analyzing the interaction among different users, each of information is based on the valuation on the sensitive information. Sensitive information are, differentiating the responsibilities of different users with respect to security, this would provide some of useful insights into the study of PPDM. Keywords: Data mining, privacy preserving data mining (PPDM), sensitive information, state-of-the-art approaches

INTRODUCTION Nowadays, the many industrial areas and governments around the world are experiencing unprecedented increase by three different things, they are volume, variety and velocity of information, it is reason to the deployment of the mobile networks of new generations and number of increased use of smart phones. There is explosion in numbers of subscribers, the services offered by the multitude, online transactions and the rise of social media. The consideration of massive data is a gold mine that must be tapped to enjoy, to do this, the appropriate technology proves by the big data [1]. This big data allows data analysis in immeasurable depths, highlights the hidden meanings in data tsunami, by showing correlations brings up the information, unsuspected association by the underlying mechanisms and shows things in a new and unexpected angle [1]. The big data will differentiate themselves from their competitors, gain market share, achieve key

objectives, increase revenue and benefit from new innovative services in the field of business organizations. Here, the big data technology is introduced along with its importance and its uses in the modern world and its key fields and substantial issues have also been highlighted. Data mining has attracted more and more attention in the recent days, it is because of the popularity of the â&#x20AC;&#x153;big data'' concept. Data mining is the process of inventing or searching interesting patterns and knowledge from many numbers of large amounts of data [2]. Data mining has been successfully applied to many domains such as business intelligence, web search, scientific discovery, digital libraries etc., it is because of its usage as a highly application-driven discipline.

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ISSN 2393-8730 (Online)

Journal of Advanced Database Management & Systems (JoADMS) Septemberâ&#x20AC;&#x201C;December 2016

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