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Node Localization Optimization in WSNS by Using Cat Swarm Optimization Meta-Heuristic

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Abstract

This paper proposed a new localization algorithm called centroid localization algorithm based on cat swarm optimization algorithm (CLA-CSO). In this algorithm, the Centroid Localization Algorithm is combined with the cat swarm optimization meta-heuristic to improve the localization accuracy in WSNs. CLA-CSO algorithm is a range free localization algorithm which consists of two stages. In the first stage, the CLA algorithm is run and the initial positions of unknown sensor nodes are estimated. In the second stage, the CSO meta-heuristic uses the initial positions found by the CLA to generate the cats of the initial population. Finally, the CSO meta-heuristic is run and the final positions of cat are considered as optimal locations of unknown sensor nodes. Simulation results show that the CLA-CSO algorithm gives good results compared with the basic CLA in terms of localization accuracy.

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Authors and Affiliations

  1. Research Unit LAMOS, Faculty of Exact Sciences, University of Bejaia, 06000, Bejaia, Algeria

    Lalama Zahia & Boulfekhar Samra

  2. Mechatronics Laboratory-E1764200, Optics and Precision Mechanics Institute, University of Setif 1, 19000, Setif, Algeria

    Semechedine Fouzi

Authors
  1. Lalama Zahia
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  2. Semechedine Fouzi
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  3. Boulfekhar Samra
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Correspondence to Lalama Zahia.

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Lalama Zahia, Fouzi, S. & Samra, B. Node Localization Optimization in WSNS by Using Cat Swarm Optimization Meta-Heuristic. Aut. Control Comp. Sci. 57, 177–184 (2023). https://doi.org/10.3103/S0146411623020104

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