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Hybrid algorithm optimization for coverage problem in wireless sensor networks

Author

Listed:
  • Han-Dong Jia

    (Shandong University of Science and Technology)

  • Shu-Chuan Chu

    (Shandong University of Science and Technology)

  • Pei Hu

    (Shandong University of Science and Technology
    Nanyang Institute of Technology)

  • LingPing Kong

    (VŠB-Technical University of Ostrava)

  • XiaoPeng Wang

    (Shandong University of Science and Technology)

  • Václav Snášel

    (VŠB-Technical University of Ostrava)

  • Tong-Bang Jiang

    (Dalian Maritime University)

  • Jeng-Shyang Pan

    (Shandong University of Science and Technology
    Chaoyang University of Technology)

Abstract

With the continuous development of evolutionary computing, many excellent algorithms have emerged, which are applied in all walks of life to solve various practical problems. In this paper, two hybrid fish, bird and insect algorithms based on different architectures are proposed to solve the optimal coverage problem in wireless sensor networks. The algorithm combines the characteristics of three algorithms, namely, particle swarm optimization algorithm, Phasmatodea population evolution algorithm and fish migration optimization algorithm. The new algorithm has the advantages of the three algorithms. In order to prove the effectiveness of the algorithm, we first test it on 28 benchmark functions. The results show that the two hybrid fish, bird and insect algorithms with different architectures have significant advantages. Then we apply the proposed algorithm to solve the coverage problem of wireless sensor networks through experimental simulation. The experimental results show the advantages of our proposed algorithm and prove that our proposed hybrid fish, bird and insect algorithm is suitable for solving the coverage problem of wireless sensor networks.

Suggested Citation

  • Han-Dong Jia & Shu-Chuan Chu & Pei Hu & LingPing Kong & XiaoPeng Wang & Václav Snášel & Tong-Bang Jiang & Jeng-Shyang Pan, 2022. "Hybrid algorithm optimization for coverage problem in wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 80(1), pages 105-121, May.
    • Handle: RePEc:spr:telsys:v:80:y:2022:i:1:d:10.1007_s11235-022-00883-5
    DOI: 10.1007/s11235-022-00883-5
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    References listed on IDEAS

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    1. Akhilesh Panchal & Rajat Kumar Singh, 2021. "EHCR-FCM: Energy Efficient Hierarchical Clustering and Routing using Fuzzy C-Means for Wireless Sensor Networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 76(2), pages 251-263, February.
    2. Jeng-Shyang Pan & Zhenyu Meng & Shu-Chuan Chu & Hua-Rong Xu, 2017. "Monkey King Evolution: an enhanced ebb-tide-fish algorithm for global optimization and its application in vehicle navigation under wireless sensor network environment," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 65(3), pages 351-364, July.
    3. Turki Ali Alghamdi, 2020. "Energy efficient protocol in wireless sensor network: optimized cluster head selection model," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 74(3), pages 331-345, July.
    4. Kavita Jaiswal & Veena Anand, 2021. "A QoS aware optimal node deployment in wireless sensor network using Grey wolf optimization approach for IoT applications," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 78(4), pages 559-576, December.
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