Energy-Efficient Node Localization Algorithm Based on Gauss-Newton Method and Grey Wolf Optimization Algorithm: Node Localization Algorithm

Energy-Efficient Node Localization Algorithm Based on Gauss-Newton Method and Grey Wolf Optimization Algorithm: Node Localization Algorithm

Amanpreet Kaur, Govind P. Gupta, Sangeeta Mittal
Copyright: © 2022 |Pages: 27
DOI: 10.4018/IJFSA.296591
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Abstract

Node localization process is a crucial prerequisite in the area of Wireless Sensor Networks (WSNs). The algorithms for node localization process can either range-based or range-free. Range-free algorithms are preferred over range-based ones due to their cost-effectiveness. DV-Hop along with its variants is normally well-liked range-free algorithm because of its straightforwardness, scalability and distributed nature, but it has some disadvantages such as poor accuracy and high-power utilization. To deal with these limitations, this paper introduces an algorithm, called GWOGN-LA. GWOGN-LA improves accuracy by applying Grey-Wolf Optimization and Gauss-Newton method. The proposed algorithm restricts the forwarding of packets in order to limit energy consumption. Simulation results show that given proposal outperforms other state-of-art algorithms in terms of accuracy and power consumption.
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1. Introduction

A WSN is a network containing numerous sensor nodes and one or more base station nodes. Sensor nodes observe various physical attributes from the surroundings, process the observed data and transmit it through wireless links(Liu, H., Nayak, A. and Stojmenovic, I., 2010)(Vidyasagar, P., Sharif, A. and Chang, 2009)(Singh, S., Chand, S. and Kumar, B., 2016). This observed data is passed via multi-hop(i.e. through neighbour nodes) communication to the base station for use (Rawat, P., Singh, K.D., Chaouchi, H. and Bonnin, J.M., 2014)-(Zhao, M. and Yang, Y., 2012). In WSNs, sensor nodes are not generally aware of their location due to random deployment like air-dropping in harsh environments.

WSNs can be applied in many areas (Vidyasagar, P., Sharif, A. and Chang, 2009)(Chaudhary, A., Peddoju, S.K. and Kadarla, K., 2017). In most of these applications, in addition to event detected by sensor node, information about location of a sensor node is also requisite. The node localization process is about finding relative/absolute location of sensor nodes within the deployed domain. Accurate node localization has several advantages including the ones mentioned below (Karl, H. and Willig, 2005)- (Sohraby, K., Minoli, D. and Znati, T., 2007):

  • 1.

    Useful in point-of-event detection in many location-sensitive applications.

  • 2.

    Useful in efficient design of various networking tasks (geographical routing, clustering, etc.).

  • 3.

    Useful for improved network monitoring and management tasks.

Most simple solution is to physically provide each node with Global Positioning System(GPS)-based location-finding unit(Peng, R., Sichitiu, M. L., 2006). Due to high accuracy, GPS seems to be a very reliable solution(Cheng et al., 2011). However, it has some disadvantages (Wang, L. and Xu, Q., 2010):

  • 1.

    GPS cannot be used in particular environments (indoors, dense forest or underwater) Also, its accuracy gets hampered because of numerous blockages(tall buildings or hills)(Selmic, R.R., Phoha, V.V. and Serwadda, A., 2016).

  • 2.

    Equipping each node with GPS in WSNs comprising thousands of sensor nodes is pretty costly(Ramadurai, V. and Sichitiu, M.L., 2003).

  • 3.

    A lot of energy consumption is required with the use of GPS (Niewiadomska-Szynkiewicz, E., 2012)-(Pal, A., 2010).

In literature, an alternate solution for localization of the node has been proposed where few sensor nodes called anchor nodes are believed to have prior awareness about their position. Anchors are used to localize other unsettled or unknown sensor nodes.

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