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Localization Optimization in WSNs Using Meta-Heuristics Optimization Algorithms: A Survey

Localization Optimization in WSNs Using Meta-Heuristics Optimization Algorithms: A Survey In Wireless Sensor Networks, node localization is one of the most important system parameters. Determining the exact position of nodes in these networks is one of vital and tedious tasks. This paper presents a review of the most localization methods which optimize the localization error. It provides a new taxonomy of techniques used in this field, including Mobile Anchor, Machine Learning, Matematical Models and Meta-heuristics. In this later, we survey its different algorithms such as Genetic Algorithm, Particle Swarm optimization, Ant Colony Optimization, BAT optimization algorithm, Firefly Optimization Algorithm, Flower Pollination Algorithm, Grey Wolf Optimization algorithm, Artificial Bees Colony Optimization Algorithm, Fish Swarm Optimization Algorithm and others. Further, the comparison between these metaheuristics algorithms based localization optimization is done. Finally, a comprehensive discussion of the performance parameters such as accuracy, convergence rate, energy consumption and the number of localized nodes is given. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Wireless Personal Communications Springer Journals

Localization Optimization in WSNs Using Meta-Heuristics Optimization Algorithms: A Survey

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References (67)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021
ISSN
0929-6212
eISSN
1572-834X
DOI
10.1007/s11277-021-08945-8
Publisher site
See Article on Publisher Site

Abstract

In Wireless Sensor Networks, node localization is one of the most important system parameters. Determining the exact position of nodes in these networks is one of vital and tedious tasks. This paper presents a review of the most localization methods which optimize the localization error. It provides a new taxonomy of techniques used in this field, including Mobile Anchor, Machine Learning, Matematical Models and Meta-heuristics. In this later, we survey its different algorithms such as Genetic Algorithm, Particle Swarm optimization, Ant Colony Optimization, BAT optimization algorithm, Firefly Optimization Algorithm, Flower Pollination Algorithm, Grey Wolf Optimization algorithm, Artificial Bees Colony Optimization Algorithm, Fish Swarm Optimization Algorithm and others. Further, the comparison between these metaheuristics algorithms based localization optimization is done. Finally, a comprehensive discussion of the performance parameters such as accuracy, convergence rate, energy consumption and the number of localized nodes is given.

Journal

Wireless Personal CommunicationsSpringer Journals

Published: Jan 1, 2022

Keywords: Wireless sensor networks; Localization; Localization optimization; Meta-heuristics

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