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Node Localization Optimization in WSNS by Using Cat Swarm Optimization Meta-Heuristic
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....
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Published in: | Automatic control and computer sciences 2023-04, Vol.57 (2), p.177-184 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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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ISSN: | 0146-4116 1558-108X |
DOI: | 10.3103/S0146411623020104 |