Journal of Mobile Computing, Communications & Mobile Networks vol 3 issue 3 by STM Journals

ISSN 2349-901X (Online)

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Mobile Computing, Communications & Mobile Networks (JoMCCMN) Septemberâ&#x20AC;&#x201C;December 2016

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Journal of Mobile Computing, Communications & Mobile Networks ISSN: 2349-901X (online)

Focus and Scope Covers 

Cellular Networks

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Channel allocation, multiple access, Location management , Handoffs

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Wireless Transmission Basics

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MAC Protocols, Routing, Transport, Sd-hoc

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Networking GSM, HSCSD, GPRS

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Satellite and Broadcast Systems

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Mobile Internet Protocols

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It is my privilege to present the print version of the [Volume 3 Issue 3] of our Journal of Mobile Computing, Communications & Mobile Networks, 2016. The intension of JoMCCMN is to create an atmosphere that stimulates vision, research and growth in the area of Mobile Computing. 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 Mobile Computing, Communications & Mobile Networks

Contents

1. Analysis and Comparison of Optimization Techniques for Interference Duration in Cognitive Radio Amit Kumar Vijay, Indu Saini, Ashish Raman

2. A Review on Clustering Approach on VANET Satendra Kumar Bansal

3. Efficient Multicast Routing in Mobile Ad hoc Network Kinjal U. Adhvaryu, Pariza Kamboj

4. An Encounter Based Routing Mechanism to Improve Delivery Ratio and Reduced Overhead Ratio in Opportunistic Networks Nidhi, Karishma

5. Solar Power Scavenging for Wireless Sensor Networks Piyush Charan, Mohd Maroof Siddiqui, Nupur Mittal, Zohaib Hasan Khan

Journal of Mobile Computing, Communications & Mobile Networks ISSN: 2349-901X (online) Volume 3, Issue 3 www.stmjournals.com

Analysis and Comparison of Optimization Techniques for Interference Duration in Cognitive Radio Amit Kumar Vijay*, Indu Saini, Ashish Raman Department of Electronics and Communication Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India Abstract Cognitive radio provides opportunity to unlicensed users to use the licensed spectrum when it is not being used. Cognitive radio has several common radio performance parameters, out of which here we analyze the interference duration. Here we used genetic algorithm, particle swarm algorithm, bat algorithm based optimization techniques for the optimization of interference duration in cognitive radio. Interference duration converges to 3.08, 1.7 and 0.1534 Âľs corresponding to genetic algorithm, particle swarm algorithm and bat algorithm and corresponding sensing efficiencies are 32.52821, 32.7471 and 32.97671%. The comparative study reveals that the optimization result of interference duration obtained from bat algorithm is more optimum as compared to genetic algorithm and particle swarm optimization, which results into higher sensing efficiency. Keywords: Cognitive radio, generation, optimization

INTRODUCTION

Cognitive radio is an efficient technique for effective use of spectrum [1]. It is an intelligent radio that can be designed and modified dynamically. Its trans-receiver is designed to utilize the best wireless channel in its region. It is a system with the capability of sensing and decision making [2]. Recent cognitive radio development is mainly focused on spectrum access where unlicensed user can also use the licensed user spectrum when it is not using the allocated spectrum. Licensed users are known as primary users (PU) and unlicensed are known as secondary users (SU). Most of the part of spectrum is distributed to numerous users through different wireless principles. Occupancy of spectrum in between the different wireless applications is not uniformly dispersed [3]. Dynamic spectrum access (DSA) technology has more ability to increase the utilization ratio of available resources as compared to static spectrum [4]. One of the important requirements in the implementation of DSA technique is to minimize the interference between secondary and primary users [5]. In optimization, we try to find the optimal value of fitness function or objective function. Many algorithms are proposed for

optimization of unconstrained optimization problems. Here we are using genetic algorithm, particle swarm optimization and bat algorithm for the optimization of interference duration in cognitive radio. Bat algorithm is comparatively new algorithm; in this algorithm batsâ&#x20AC;&#x2122; position gives the possible solution of an algorithm. It is more powerful than GA and PSO. It has good combination of advantages of these algorithms. The rest of the paper is organized as follows: In the next part of the paper, we present a brief introduction of genetic algorithm, particle swarm optimization and bat algorithm; followed by the performance objective, system model, the effect of optimization of interference duration on spectrum sensing efficiency and finally the concluding remarks. Genetic Algorithm It is biologically inspired search method that works well in problems with large spaces. GA does not process a single solution; instead it works on a population of solutions in parallel at a time. Figure 1 shows the basic flow chart for genetic algorithm [6].

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Journal of Mobile Computing, Communications & Mobile Networks

ISSN: 2349-901X(online) Volume 3, Issue 3 www.stmjournals.com

A Review on Clustering Approach on VANET Satendra Kumar Bansal* Department of Computer Science, Vikrant Institute of Technology and Management, Gwalior, Madhya Pradesh, India Abstract Vehicular ad hoc network is growing area of research where it provides intelligent transportation system. In this paper, we study about VANET and its clustering approach. There is lots of work done in this field, but we have focused on clusters because by using clusters, communication becomes fast. Keywords: VANET, ITS, ATM

INTRODUCTION

VANET is a special MANET kind in which nodes are vehicles that move at high speed and use brief-range communication. A VANET is utilized in many business applications equivalently offering effective routing information to the further vehicles, notifying the drivers about the road traffic conditions, mishaps, road circumstances and so on. VANET creates utilize of a lot of sensor devices; they are employed to realize the network conditions that help for making a decision. All devices are fit for social occasion relevant information and disseminate the data to other sensors. These low rate sensor devices are very small, and they can be utilized in a big numbers in the network without incurring high financial expenditures. VANET is a structure-less network containing cell nodes which communicate between themselves through a wireless medium. The nodes communicate with each other without the help of base-station. Secured information dissemination is a difficult mission in this sort of networks. Revealing confidential information to an un-meant receiver may harm the advantages that would be obtained from the VANETs [1].

CHARACTERISTICS OF VANET

Vehicular networks have certain unusual type of behavior and characteristics, which recognizes them from different sorts of networks. In contrast with different networks, this network has unique and interesting features as follow (Figure 1).

Fig. 1: Vehicular Ad Hoc Network. Unlimited Transmission Power In the ad hoc devices, power issue is a fundamental obligation, yet on account of this network, nodes/vehicles give constant and adequate energy for processing and specialized devices for doing other assignment. Computational Limit High Operating vehicles can have very significant computing capacity which is done by sensors and circuits in the vehicles with sufficient energy and sensing capabilities. Predictable Mobility and Communication In the VANET, where mobility of the vehicle is very tough to predict, vehicles have most predictable activities that are controlled to roadways. Roadways information is often displayed from situating frameworks and map based technologies, for example GPS. It can give brief information about the vehicle

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Journal of Mobile Computing, Communications & Mobile Networks ISSN: 2349-901X (online) Volume 3, Issue 3 www.stmjournals.com

Efficient Multicast Routing in Mobile Ad hoc Network 1

Kinjal U. Adhvaryu1,*, Pariza Kamboj2

Department of Computer Engineering, RK University, Rajkot, Gujarat, India Department of Computer Engineering, Sarvajanik College of Engineering and Technology, Surat, Gujarat, India

Abstract Mobile ad hoc network (MANET) is dynamic, self-configuring, distributive, infrastructure-less and self-organized wireless network having collection of independent mobile nodes which are free to move arbitrarily. MANET uses a multicast communication in various applications in which close collaboration of teams is very crucial. In this paper, we propose optimized expanding ring search (OERS) protocol which uses modified expanding ring search method during route discovery process and also analyse the performance of proposed protocol and multicast ad hoc on demand distance vector (MAODV) routing protocol for varying node speed parameter value. For experiment purpose, we have also considered different numbers of receiver nodes in multicast group. Using different performance metrics like, normalized routing load, throughput, end-to-end delay and packet delivery ratio, performance comparison has also been conducted for varying node speed and varying number of receiver nodes. It has been observed that performance of OERS and MAODV protocols is affected by the node speed value and number of receiver mobile nodes in the multicast group. Considering all scenario results, OERS outperforms the MAODV. Keywords: MANET, control overhead, multicasting, shared tree, end-to-end delay

INTRODUCTION

Mobile ad hoc network (MANET) is dynamic, infrastructure-less, self-configuring, selforganized and distributive wireless networks having collection of independent mobile nodes which are free to move arbitrarily. However, as a result of these characteristics of MANET, it has to face many challenges and one of them is the packet routing. Lot of work has been done in this area of ad hoc routing and various protocols are designed to fulfil the requirement of various applications. These all routing protocols are basically categorized into two types: reactive type and proactive types of protocol. Reactive type of protocols which are also known as on demand routing protocol update their routing table entries as and when routing of packets is required. Proactive types of protocols update their routing table entries periodically. Because of this basic characteristic, there is a significant difference in performance of both types of protocol under similar situation. And because of this reason we can say that performance of routing is largely depending on selection of

protocol. Multicasting in MANET can be defined as data transmission from source node to multiple receiver nodes simultaneously. Due to this characteristic, it reduces the communication cost in terms of utilization of channel bandwidth; reduces processing of sender and router node, memory utilization and various types of delays. Multicast routing protocols are classified basically into two categories: first is source based tree multicast routing protocol and second is group shared tree multicast routing protocol. In the former approach, routing tree is created by each sender node individually in the multicast group and the latter approach creates a single routing tree for complete multicast group. Many of the simulations have already being done by various researchers using various performance metrics like goodput, delay, remaining node energy, normalized routing load, jitter, response time and packet delivery ratio. Many of them have considered variation of simulation scenarios like number of communication nodes, simulation duration time, existing traffic pattern, node mobility

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Journal of Mobile Computing, Communications & Mobile Networks

ISSN: 2349-901X(online) Volume 3, Issue 3 www.stmjournals.com

An Encounter Based Routing Mechanism to Improve Delivery Ratio and Reduced Overhead Ratio in Opportunistic Networks Nidhi*, Karishma

Department of Computer Science and Applications, Kurukshetra University, Kurukshetra, Haryana, India

Abstract OPPNETs (Opportunistic Networks) are wireless networks that have sporadic network connectivity, thus rendering the existence of instantaneous end-to-end paths from a source to a destination difficult or impossible. Hence, in such networks, message delivery relies heavily on the store-and-forward paradigm to route messages. However, limited knowledge of the contact times between the nodes poses a big challenge to effective forwarding of messages. In this paper, EBR (encounter based routing) is proposed that focuses on algorithm to measure contacts between nodes and measure most favorable node. The contact is calculated between two nodes when they come in range of each other. The aim of proposed scheme is to reduce replication of messages. The proposed mechanism is implemented using ONE simulator. Simulation results show that proposed mechanism has less message delay, less replication of messages and less average buffer time. Keywords: OPPNETs (Opportunistic Networks), epidemic routing, EBR (Encounter Based Routing), ONE (Opportunistic Networks Environment)

INTRODUCTION

An OPPNET is a network designed to operate effectively in highly-challenged environments where protocols adopted in connected networks (i.e. TCP/IP) fail. Opportunistic networks (OPPNET) represent a class of networks that experience long delays and intermittent connectivity [1]. The OPPNET is a class of fault-tolerant network, where end-toend connections are not required for routing of the message from source to the destination. In opportunistic networks (OPPNETs), messages are transmitted hop-by-hop from one network node to another until the destination is reached. In challenging environment, message transfers through intermediate nodes. To choose next intermediate node for transmission of messages in network is a typical task. To transmit messages, various routing protocols like direct delivery routing, epidemic routing and spray and wait routing are available [2]. In epidemic routing, messages are replicated over the whole network and delivered to intermediate node. When messages are

replicated over the network then it increases delivery ratio but also creates overhead in the network [3]. In spray and wait routing, the messages are flooded over the nodes in the network and wait for the reply. After getting reply from one node, message would transfer through that node in the network but at the same time too much delay was created in network. Architecture of OPPNET There are many bundle protocol implementations, but the most famous protocol is OPPNET, that is developed by Intel and at present it is maintained by Dublin Trinity College, and ION (Interplanetary Overlay Network) [4]. The essence of the bundle protocol lies in the fact that all information data and control signals are combined in a single atomic entity, called bundle, which is transmitted across an OPPNET. Figure 1 shows the modified fivelayer internet protocol stack that includes the bundle layer. An overlay is located in between the application layer and the transport layer.

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Journal of Mobile Computing, Communications & Mobile Networks

ISSN: 2349-901X(online) Volume 3, Issue 3 www.stmjournals.com

Solar Power Scavenging for Wireless Sensor Networks Piyush Charan*, Mohd Maroof Siddiqui, Nupur Mittal, Zohaib Hasan Khan Department of Electronics and Communication Engineering, Integral University, Lucknow, Uttar Pradesh, India Abstract Energy scavenging (also known as energy harvesting or ambient power) is a major challenge for scientists to overcome in small, wireless autonomous electronic devices like those used in wearable electronics and wireless sensor networks. As of today, solar energy is the cleanest vitality source available in abundance. This fact has interested the researchers, industries and consumers to develop technology that can harvest solar energy and can possibly convert to useful electrical energy. As we probably are aware, that a node/mote in a wireless sensor network works on AA size battery of 3 V and works up to a life of almost 3 years and it is very difficult to change the on-board battery of a node while it is active in a particular sensing activity. So to sustain the node in a network for the maximum time we need to explore different energy scavenging schemes, of which solar energy scavenging seems to be the most promising. The enhancing research in photovoltaic (PV) application has demonstrated that photovoltaic renewable vitality is considered as a standout amongst the most encouraging source to support the increasing demand in electrical utilization. In this paper, we propose to utilize the solar photovoltaic energy to power a sensor node in a network so that the node may be able to compensate for the energy lost for transmission and reception and at the same time remain active in the network. The paper shows that incorporating the solar status of nodes in the routing decision is feasible by using a solar aware routing protocol (SARP) and it results in reduced overall battery consumption. Keywords: Solar energy, photovoltaic, SARP, energy scavenging, WSNs

INTRODUCTION

The application of photovoltaic (PV) systems is well known for stand-alone applications but until recent years there has been a vast increment in the application of solar energy for wireless sensor networks (WSNs). Maurya et al. have stated that near about 15 mW/cm3 of photovoltaic power can be harvested from solar energy for wireless sensors [1]. PV modules are exposed to the sunlight to capture the solar radiation to generate the direct current (DC) electricity. Storage system is used to capture all the converted solar radiation into usable energy to power wireless nodes active in a sensing environment. Solar PV systems can be categorized into two end-user technologies based on application of the technology. There are two types of solar PV system, mainly known as grid-tied (gridconnected) and standalone (off-grid) solar PV systems. Grid-tied solar PV system is mainly connected to the national main power grid

distribution system. This type of solar PV systems is usually installed or mounted on the building roof and sometimes integrated into the building. Recently, various technological advancements in nanotechnology, plasmonics, metamaterials, photonics and semiconducting polymer studies had offered cost efficient photovoltaics based on new technology. The first generation of solar cells based on crystalline silicon is the first to offer photovoltaic energy conversion [2]. Multijunction solar cells are newer technologies that are capable of generating double as much power under the same conditions as the conventional solar cells [1]. But multi-junction type of solar cells is way too expensive and can be employed only in applications requiring high performance such as in satellites. Routing in wireless sensor networks has to take into account the very limited resources of the nodes. Although many researchers assume that all nodes in a sensor network are battery-

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ISSN 2349-901X (Online)

Journal of

Mobile Computing, Communications & Mobile Networks (JoMCCMN) Septemberâ&#x20AC;&#x201C;December 2016

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