Salp Swarm Algorithm for Node Localization in Wireless Sensor Networks

Nodes localization in a wireless sensor network (WSN) aims for calculating the coordinates of unknown nodes with the assist of known nodes. The performance of a WSN can be greatly affected by the localization accuracy. In this paper, a node localization scheme is proposed based on a recent bioinspir...

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Bibliographic Details
Main Authors: Huthaifa M. Kanoosh, Essam Halim Houssein, Mazen M. Selim
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Journal of Computer Networks and Communications
Online Access:http://dx.doi.org/10.1155/2019/1028723
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Summary:Nodes localization in a wireless sensor network (WSN) aims for calculating the coordinates of unknown nodes with the assist of known nodes. The performance of a WSN can be greatly affected by the localization accuracy. In this paper, a node localization scheme is proposed based on a recent bioinspired algorithm called Salp Swarm Algorithm (SSA). The proposed algorithm is compared to well-known optimization algorithms, namely, particle swarm optimization (PSO), Butterfly optimization algorithm (BOA), firefly algorithm (FA), and grey wolf optimizer (GWO) under different WSN deployments. The simulation results show that the proposed localization algorithm is better than the other algorithms in terms of mean localization error, computing time, and the number of localized nodes.
ISSN:2090-7141
2090-715X