Coverage optimization of wireless sensor networks based on improved fruit fly optimization algorithm

Dehui Zheng; Guifen Chen; Guangjiao Chen

doi:10.1117/12.2685596

28 July 2023 Coverage optimization of wireless sensor networks based on improved fruit fly optimization algorithm

Dehui Zheng, Guifen Chen, Guangjiao Chen

Proceedings Volume 12716, Third International Conference on Digital Signal and Computer Communications (DSCC 2023); 1271611 (2023) https://doi.org/10.1117/12.2685596
Event: Third International Conference on Digital Signal and Computer Communications (DSCC 2023), 2023, Xi'an, China

Abstract

In order to solve the problem of low network coverage due to random deployment of nodes in wireless sensor networks (WSN), this paper proposes an Improved Fruit Fly Optimization Algorithm (IFOA) and uses the network coverage as the algorithm optimization objective function. First, a Tent chaotic mapping is used to initialize the population so that the initial population individuals are diverse. Second, a linear decay step strategy is used to balance the global search in the first stage of the algorithm and the local search in the second stage. Finally, the optimal fruit fly individuals are perturbed by the Cauchy mutation to prevent the algorithm from falling into a local optimum. And the algorithm is applied to the wireless sensor network coverage optimization problem. Simulation results show that the algorithm effectively improves the network coverage, reduces node redundancy, and makes the network have higher coverage performance.

Citation Download Citation

Dehui Zheng, Guifen Chen, and Guangjiao Chen "Coverage optimization of wireless sensor networks based on improved fruit fly optimization algorithm", Proc. SPIE 12716, Third International Conference on Digital Signal and Computer Communications (DSCC 2023), 1271611 (28 July 2023); https://doi.org/10.1117/12.2685596

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