Multi-Objective Optimization for Node Deployment of 3D Curved Surface Wireless Sensor Networks

In researching wireless sensor networks (WSNs), node deployment for three-dimensional (3D) curved scenarios is challenging. This study aims to develop a node deployment strategy for 3D curved surface WSNs with high coverage, good connectivity, low energy consumption, and long lifespan. Firstly, a 3D curved surface (mountain) model and a sensing model with the attenuation of perception ability when encountering obstacles are established. Secondly, a joint deployment scheme for sensor and relay nodes is proposed to reduce the likelihood of energy-hole occurrence and the complexity of the entire network deployment. A multiobjective node deployment (MOND) model with connectivity ratio as a constraint and maximum coverage and minimum energy consumption as optimization objectives are constructed. Finally, to address this MOND problem, this article proposes two algorithms based on Pareto optimal and hunter-prey optimization: Multi-objective Hunter-Prey Optimization Algorithm (MOHPO) and Multi-objective Hunter-Prey Optimization Algorithm with Fuzzy C-Means Clustering (MOHPO/FCM). Simulation experiments were conducted in both multi-peak and multi-depression terrain scenarios to evaluate the node deployment performance of the proposed algorithm. Simulation results show that MOHPO and MOHPO/FCM exhibit superior performance in improving network coverage, enhancing connectivity, reducing energy consumption, and extending network lifespan compared to the comparison algorithms.