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IRO Journal on Sustainable Wireless Systems

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Home / Archives / Volume-2 / Issue-4 / Article-6

Volume - 2 | Issue - 4 | december 2020

Novel Distance Estimation based Localization Scheme for Wireless Sensor Networks using Modified Swarm Intelligence Algorithm
Pages: 171-176
Published
12 January, 2021
Abstract

Wireless sensor networks (WSN) consists of a huge number of nodes that are positioned randomly to obtain information regarding the environment and communicate with each other. On detection of an event, obtaining information regarding the geographical location of the sensor is beneficial in most applications. Range-free and range-based localization schemes are the major categories of localization algorithms available. Range-free localization algorithms utilize the connectivity information to provide a cost efficient localization solution. On the other hand, range-based localization schemes use radio signal strength and distance from anchor nodes for estimating the unknown node location. Several swarm intelligence algorithms are used for reducing the noise while optimizing localization and distance estimation while using these schemes. In this paper, we propose an enhanced swarm intelligence scheme that provides better performance when compared to the existing algorithms in terms of noise level, signal strength, number of anchors, number of nodes, radio signal strength and localization error. Surrogate based optimization (SBO), firefly algorithm (FA), butterfly optimization algorithm (BOA), genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are compared with the proposed scheme.

Keywords

Localization Wireless Sensor Networks swarm intelligence algorithm distance estimation nature inspired algorithms

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