Author(s)

Shuang Shan ¹

Affiliation(s)

¹ College of Science, North China University of Technology, Beijing, 100000, China

Corresponding Author

Shuang Shan

ABSTRACT

Coverage optimization is one of the basic problems in wireless sensor networks. Coverage reflects the service quality provided by wireless sensor networks. Swarm intelligence algorithm is an optimization method inspired by natural organisms. Node coverage optimization is also an optimization problem. Swarm intelligence algorithm can solve the coverage problem of wireless sensor networks. Therefore, this paper focuses on the application of swarm intelligence algorithm in coverage optimization of wireless sensor networks, and proposes a coverage optimization strategy based on swarm intelligence algorithm: coverage optimization of three-dimensional wireless sensor networks based on equilibrium optimization algorithm. In this algorithm, the principle is to control the volume and mass balance model, the particle concentration update according to the equilibrium candidate solution, and finally reach the equilibrium state, which mainly consists of three stages: population initialization, equilibrium pool and concentration update. In the simulation, the equilibrium optimization algorithm has higher effective coverage than the particle swarm optimization algorithm.

KEYWORDS

Balanced optimization algorithms, wireless sensor networks, coverage, three-dimensional space

CITE THIS PAPER

Shuang Shan, Optimization of 3D WSN coverage based on equilibrium optimization algorithm. Journal of Artificial Intelligence Practice (2023) Vol. 6: 39-47. DOI: http://dx.doi.org/10.23977/jaip.2023.060305.

REFERENCES

[1] Zhang Qian. Research on Coverage Optimization of wireless Sensor Networks Based on Swarm Intelligence Algorithm [D]. Hunan University, 2015.
[2] Fu Bo, Huang Xiaoxiao, Zhao Xilin et al. WSN coverage optimization based on adaptive nonlinear factor weed algorithm [J]. Journal of Hubei University of Technology, 2023, 38(02):7-10+26.
[3] Afshin Faramarzi, Mohammad Heidarinejad, Brent Stephens, Seyedali Mirjalili. Equilibrium optimizer:  A novel optimization algorithm [J]. Knowledge-Based Systems, 2020, 191.
[4] Yang Lei, Li Shengnan, Huang Wei, Zhang Dan, Yang Bo, Zhang Xiaoshun. Reactive power Optimization of high-proportion wind-power new energy Grid based on Balance optimizer [J/OL]. Journal of electric power system and its automation: 1-9 [2020-12-18]. https://doi.org/10.19635/j.cnki.csu-epsa.000555.
[5] Li Shouyu, He Qing, Chen Jun. Application Research of Computers, 2022, 39(4): 1168-1172+1189.

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