A Node Deployment Method Based on Improved Snake Optimizer for Marine Disasters

Underwater acoustic sensor networks (UASNs) have demonstrated remarkable potential in marine environmental monitoring. However, current research on node deployment methods aiming at disaster scenarios is insufficient, and few studies have paid attention to the spatial distribution characteristics of marine disasters in underwater areas, making it difficult to achieve effective monitoring. In addition, UASNs encounter the challenge that the energy of nodes is restricted and arduous to recharge. In this article, we propose a node deployment method based on improved snake optimizer (DMISO) for marine disasters. First, on the basis of analyzing the spatial distribution characteristics of common marine disasters, a hierarchical deployment method based on analytic hierarchy process (AHP) is proposed to meet the monitoring requirements of target areas. Then, in order to reduce energy consumption, an improved snake optimizer (ISO) based on opposition-based learning (OBL) is used to optimize the deployment location of nodes with the joint optimization objective of network coverage and total energy consumption. After that, a path allocation strategy (PAS) is proposed to reallocate a reasonable target location for each node so as to equalize energy consumption across all nodes. The simulation results show that DMISO reduces energy consumption by 35.46% compared to underwater fruit fly optimization algorithm (UFOA). Coverage is improved by an average of 4.77% and 17.4%, compared to UFOA and random deployment. In addition, DMISO has significant advantages in equalizing energy consumption and can effectively extend the network lifetime.