A hybrid-strategy-improved butterfly optimization algorithm applied to the node coverage problem of wireless sensor networks

Donghui Ma; Qianqian Duan; Donghui Ma; Qianqian Duan

doi:10.3934/mbe.2022181

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 4: 3928-3952. doi: 10.3934/mbe.2022181

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A hybrid-strategy-improved butterfly optimization algorithm applied to the node coverage problem of wireless sensor networks

Donghui Ma ,
Qianqian Duan ^,

Department of Electric and Electronic Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
Academic editor: Hamid Reza Karimi

Received: 08 December 2021 Revised: 19 January 2022 Accepted: 25 January 2022 Published: 11 February 2022

To increase the node coverage of wireless sensor networks (WSN) more effectively, in this paper, we propose a hybrid-strategy-improved butterfly optimization algorithm (H-BOA). First, we introduce Kent chaotic map to initialize the population to ensure a more uniform search space. Second, a new inertial weight modified from the Sigmoid function is introduced to balance the global and local search capacities. Third, we comprehensively use elite-fusion and elite-oriented local mutation strategies to raise the population diversity. Then, we introduce a perturbation based on the standard normal distribution to reduce the possibility of the algorithm falling into premature. Finally, the simulated annealing process is introduced to evaluate the solution's quality and improve the algorithm's ability, which is helpful to jump out of the local optimal value. Through numerous experiments of the international benchmark functions, the results show the performance of H-BOA has been significantly raised. We apply it to the WSN nodes coverage problem. The results show that H-BOA improves the WSN maximum coverage and it is far more than other optimization algorithms.
- butterfly optimization algorithm,
- wireless sensor networks,
- hybrid strategy,
- optimized coverage
Citation: Donghui Ma, Qianqian Duan. A hybrid-strategy-improved butterfly optimization algorithm applied to the node coverage problem of wireless sensor networks[J]. Mathematical Biosciences and Engineering, 2022, 19(4): 3928-3952. doi: 10.3934/mbe.2022181

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Abstract

To increase the node coverage of wireless sensor networks (WSN) more effectively, in this paper, we propose a hybrid-strategy-improved butterfly optimization algorithm (H-BOA). First, we introduce Kent chaotic map to initialize the population to ensure a more uniform search space. Second, a new inertial weight modified from the Sigmoid function is introduced to balance the global and local search capacities. Third, we comprehensively use elite-fusion and elite-oriented local mutation strategies to raise the population diversity. Then, we introduce a perturbation based on the standard normal distribution to reduce the possibility of the algorithm falling into premature. Finally, the simulated annealing process is introduced to evaluate the solution's quality and improve the algorithm's ability, which is helpful to jump out of the local optimal value. Through numerous experiments of the international benchmark functions, the results show the performance of H-BOA has been significantly raised. We apply it to the WSN nodes coverage problem. The results show that H-BOA improves the WSN maximum coverage and it is far more than other optimization algorithms.

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