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An improved salp swarm algorithm for solving node coverage optimization problem in WSN

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Abstract

In order to improve the coverage of wireless sensor networks and reduce the energy consumption of node movement in secondary deployment, an improved coverage optimization algorithm based on improved Salpa swarm Intelligent algorithm (ATSSA) is proposed. Firstly, the population is initialized using tent chaotic sequence to enhance the optimization ability of the algorithm. Secondly, the T-distribution mutation is added to the update formula of the leaders for improving the ability to jump out of the local optimal value. Finally, an adaptive formula for updating the position of the follower is proposed, which not only guarantees the local searching ability of the algorithm in the late iteration period, but also improves the global searching ability of the algorithm in the early iteration period. The experimental results show that ATSSA algorithm can improve the coverage of the wireless sensor networks and reduce deployment costs compared with other algorithms, when it is used in the wireless sensor networks.

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Funding

This research was supported by the National Natural Science Foundation of China (31670554).

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Authors and Affiliations

  1. Department of Information Science and Technology, Nanjing Forestry University, Nanjing, 211037, China

    Jiaming Wang, Zhengli Zhu, Fuquang Zhang & Yanxiong Liu

Authors
  1. Jiaming Wang
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  2. Zhengli Zhu
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  3. Fuquang Zhang
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  4. Yanxiong Liu
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Contributions

Conceptualization, Jiaming Wang and Zhengli Zhu; methodology, Jiaming Wang; software, Jiaming Wang; validation, all authors; formal analysis, all authors; data curation, Jiaming Wang and Yanxiong liu; writing, Jiaming Wang and Zhengli Zhu; visualization, Fuquang Zhang and Yanxiong liu; supervision, Fuquang Zhang and Zhengli Zhu; project administration, all authors; funding acquisition, Fuquang Zhang and Zhengli Zhu. All authors reviewed the manuscript.

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Correspondence to Zhengli Zhu.

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Wang, J., Zhu, Z., Zhang, F. et al. An improved salp swarm algorithm for solving node coverage optimization problem in WSN. Peer-to-Peer Netw. Appl. 17, 1091–1102 (2024). https://doi.org/10.1007/s12083-024-01637-7

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