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A parallel compact cat swarm optimization and its application in DV-Hop node localization for wireless sensor network

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Abstract

Cat swarm optimization (CSO) has been applied to a variety of fields because of the better capacity of searching for optimum and higher robustness. However, the poor convergency and larger memory consumption are still core defects, which restricts the efficiency of optimization to a larger extent. A new heuristic algorithm named Parallel Compact Cat Swarm Optimization (PCCSO) with three separate communication strategies and the concept of the compact are presented in this article. The advantage of PCCSO is not only reflected in enhancing the ability of local search, but also in saving the computer memory. The experimental results on CEC2013 benchmark functions demonstrate that the PCCSO is always superior to PSO, CSO, and improved CSO in getting convergent. Then, the PCCSO is applied to DV-Hop to effectively improve the localization accuracy of unknown nodes while also saving WSN memory. The experimental results based on PCCSO from the different number of sensor nodes also illustrate that the PCCSO-DV-Hop shows a lower localization error compared to other optimization algorithms based on DV-Hop.

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Acknowledgements

This work is supported by National Natural Science Foundation of China (No. 61501106), Science and Technology Foundation of Jilin Province (Nos. 201801010-39JC, JJKH20200116KJ), and Science and Technology Foundation of Jilin City (No. 201831775).

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Authors and Affiliations

  1. School of Computer Science, Northeast Electric Power University, Jilin, China

    Jianpo Li, Min Gao & Jeng-Shyang Pan

  2. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China

    Jeng-Shyang Pan & Shu-Chuan Chu

  3. College of Science and Engineering, Flinders University, Clovelly Park, SA, 5042, Australia

    Shu-Chuan Chu

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  1. Jianpo Li
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  2. Min Gao
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Correspondence to Jeng-Shyang Pan.

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Li, J., Gao, M., Pan, JS. et al. A parallel compact cat swarm optimization and its application in DV-Hop node localization for wireless sensor network. Wireless Netw 27, 2081–2101 (2021). https://doi.org/10.1007/s11276-021-02563-9

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