Multi-Objective Coverage Optimization for 3D Heterogeneous Wireless Sensor Networks

Aiming at the problems of low coverage, poor connectivity, and high energy consumption in 3D heterogeneous wireless sensor networks (3D HWSNs), this article constructs a multi-objective coverage optimization model that balances coverage, connectivity, and energy consumption. Meanwhile, this article proposes a multi-objective spider wasp optimizer (MOSWO) based on a spider wasp optimizer (SWO) to solve the problem. Firstly, incorporating an external archive allows MOSWO to obtain and store Pareto optimal solutions. Secondly, 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 3D HWSNs in obstacle and noobstacle 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.