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A novel topology optimization of coverage-oriented strategy for wireless sensor networks

Author

Listed:
  • Shuxin Wang
  • Hairong You
  • Yinggao Yue
  • Li Cao

Abstract

Aiming at the key optimization problems of wireless sensor networks in complex industrial application environments, such as the optimum coverage and the reliability of the network, a novel topology optimization of coverage-oriented strategy for wireless sensor networks based on the wolf pack algorithm is proposed. Combining the characteristics of topology structure of wireless sensor networks and the optimization idea of the wolf pack algorithm redefines the group’s wandering and surprise behavior. A novel head wolf mutation strategy is proposed, which increases the neighborhood search range of the optimal solution, enhances the uniformity of wolf pack distribution and the ergodicity ability of the wolf pack search, and greatly improves the calculation speed and the accuracy of the wolf pack algorithm. With the same probability, the cluster heads are randomly selected periodically, and the overall energy consumption of wireless sensor networks is evenly distributed to the sensor node to realize the balanced distribution of the data of the member nodes in the cluster and complete the design of the topology optimization of wireless sensor networks. Through algorithm simulation and result analysis, compared with the particle swarm optimization algorithm and artificial fish swarm algorithm, the wolf swarm algorithm shows its advantages in terms of the residual energy of the sensor node, the average transmission delay, the average packet delivery rate, and the coverage of the network. Among them, compared with the particle swarm optimization algorithm and artificial fish swarm algorithm, the remaining energy of nodes has increased by 9.5% and 15.5% and the average coverage of the network has increased by 10.5% and 5.6%, respectively.

Suggested Citation

  • Shuxin Wang & Hairong You & Yinggao Yue & Li Cao, 2021. "A novel topology optimization of coverage-oriented strategy for wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 17(4), pages 15501477219, April.
    • Handle: RePEc:sae:intdis:v:17:y:2021:i:4:p:1550147721992298
    DOI: 10.1177/1550147721992298
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    References listed on IDEAS

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    1. Hu-Sheng Wu & Feng-Ming Zhang, 2014. "Wolf Pack Algorithm for Unconstrained Global Optimization," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-17, March.
    2. Seyed Mahdi Jameii & Karim Faez & Mehdi Dehghan, 2016. "AMOF: adaptive multi-objective optimization framework for coverage and topology control in heterogeneous wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 61(3), pages 515-530, March.
    3. Marta Zárraga-Rodríguez & Xabier Insausti & Jesús Gutiérrez-Gutiérrez, 2019. "On the topology design of large wireless sensor networks for distributed consensus with low power consumption," International Journal of Distributed Sensor Networks, , vol. 15(12), pages 15501477198, December.
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    Cited by:

    1. Qiang Peng & Renjun Zhan & Husheng Wu & Meimei Shi, 2024. "Comparative Study of Wolf Pack Algorithm and Artificial Bee Colony Algorithm: Performance Analysis and Optimization Exploration," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 15(1), pages 1-24, January.

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