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WSN node localization algorithm of sparrow search based on elite opposition-based learning and Levy flight

Author

Listed:
  • Xiuwu Yu

    (University of South China)

  • Wei Peng

    (University of South China)

  • Yong Liu

    (University of South China)

Abstract

In order to improve localization accuracy of localization algorithm based on received signal strength indication in wireless sensor network (WSN), a WSN node localization algorithm based on sparrow search improved by elite opposition-based learning and Levy flight (SSELF) is proposed. Firstly, the sparrow population is initialized by using the chaotic map to enhance population diversity and accelerate algorithm convergence speed. Secondly, the elite opposition-based learning strategy is applied to increase the diversity of the sparrow population and improve global search capability. Then, the Levy flight strategy is adopted to enhance the ability to jump out of local optimal solution. Finally, the SSELF is used to estimated the positions of unknown nodes.The simulation results demonstrate that the proposed SSELF outperforms the four comparison algorithms in terms of localization accuracy.

Suggested Citation

  • Xiuwu Yu & Wei Peng & Yong Liu, 2023. "WSN node localization algorithm of sparrow search based on elite opposition-based learning and Levy flight," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 84(4), pages 521-531, December.
    • Handle: RePEc:spr:telsys:v:84:y:2023:i:4:d:10.1007_s11235-023-01062-w
    DOI: 10.1007/s11235-023-01062-w
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