Localization in Wireless Sensor Networks Using Soft Computing Approach

Localization in Wireless Sensor Networks Using Soft Computing Approach

Sunil Kumar Singh (National Institute of Technology Patna, Patna, India), Prabhat Kumar (National Institute of Technology, India) and Jyoti Prakash Singh (National Institute of Technology Patna, Patna, India)
Copyright: © 2017 |Pages: 12
DOI: 10.4018/IJISP.2017070104
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Abstract

Wireless sensor network (WSN) is formed by a large number of low-cost sensors. In order to exchange information, sensor nodes communicate in an ad hoc manner. The acquired information is useful only when the location of sensors is known. To use GPS-aided devices in each sensor makes sensors more costly and energy hungry. Hence, finding the location of nodes in WSNs becomes a major issue. In this paper, the authors propose a combination of range based and range-free localization scheme. In their scheme, for finding the distance, they use received signal strength indication (RSSI), which is a range based center of gravity technique. For finding the location of non-anchor nodes, the authors assign weights to anchor and non-anchor nodes based on received signal strength. The weight, which is assigned to anchor and non-anchor nodes, are designed by fuzzy logic system (FLS).
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1. Introduction

Wireless sensor networks(WSNs) (Akyildiz, 2002) consist of a large number of tiny sized sensors having the limited processing capability, limited battery life, and limited storage capacity. WSNs enable several classes of application such as automatic data collection, habitat monitoring, military surveillance and disaster relief operations.For all these applications along with sensed data, the knowledge of location is also necessary. Location information also helps in finding routing of packets from a souce to destination nodes. One of the major options of finding location of each and every sensor nodes is using GPS in sensor nodes. However, use of GPS-aided devices in sensors make them costly and energy hungry, which restricts the usage of sensor nodes. Most of the time, the battery of sensor nodes is non-replacable and hence consumption of more energy reduces their lifetime. The better and more popular option is a use of some sensor (usually 10-15% of total deployement) equipped with GPS devices and determine the location for other sensor nodes with the help of those sensors having GPS devices.The sensor nodes having GPS devices are called as anchor nodes whereas aother normal nodes are called non-anchor nodes. We use an algorithmic approach for finding the location of the non-anchor node using the computational capability of sensor nodes. The localization algorithms can be categorized into two types (i) Range based and (ii) Range free (Akyildiz, 2002). In range based technique, we measure distance or angle between sensors for finding the location of non-anchor nodes. Range free technique does not measure distance or angle, it uses connectivity information for finding the location of the sensors. For measuring angle or distance, range based technique uses procedures such as angle of arrival (AOA) (Cong, 2002), time of arrival (TOA) (Bulusu, 2000), time difference of arrival (TDOA) (Venkatraman, 2004) and received signal strength indication (RSSI) (Li, 2006). These techniques along with triangulation (Leelavathy, 2014) or trilateration (Oguejiofor, 2013) or multilateration (Miwa 2013) technique are used for finding the location in a range based technique. Due to its simplicity, range free techniques are more popular as compared to the range based technique.

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