Multiobjective Coverage Optimization for 3-D Heterogeneous Wireless Sensor Networks

doi:10.1109/TCAD.2025.3567526

Multiobjective Coverage Optimization for 3-D Heterogeneous Wireless Sensor Networks

2025-05-06

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DOI：10.1109/TCAD.2025.3567526

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Aiming at the problems of low coverage, poor connectivity, and high energy consumption in 3-D heterogeneous wireless sensor networks (3-D HWSNs), this article constructs a multiobjective coverage optimization model that balances coverage, connectivity, and energy consumption. Meanwhile, this article proposes a multiobjective spider wasp optimizer (MOSWO) based on a spider wasp optimizer (SWO) to solve the problem. First, incorporating an external archive allows MOSWO to obtain and store Pareto optimal solutions. Second, an important-objective trend operator and improving SWO’s mating behavior enhance the algorithm’s optimization ability. Finally, A spherical divergence operator is introduced to reduce the redundancy of sensor nodes. To compare the coverage optimization performance of the proposed algorithm, MOSWO MOAAO, MOEA/D, MOPSO, MOAHA, and NSGA-II are used to solve the MCO problem of 3-D HWSNs in obstacle and no-obstacle scenes. The experimental results show that the Pareto front of MOSWO is optimal compared to the Pareto fronts of MOAAO, MOEA/D, MOPSO, MOAHA, and NSGA-II. MOSWO performs effectively in improving coverage and network connectivity, reducing energy consumption.

Keywords:

3-D heterogeneous wireless sensor networks (3-D HWSNs)

multiobjective coverage optimization (MCO)

multiobjective spider wasp optimizer (MOSWO)

Pareto optimal solutions

Multiobjective Coverage Optimization for 3-D Heterogeneous Wireless Sensor Networks

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