An Optimized Deployment Method for Underwater Wireless Sensor Networks Based on Probability Density for Node Depth Self-Adjustment

For applications requiring high node density and broad coverage, this paper introduces the area of Voronoi diagrams as sinking probabilities and proposes the Probability Density-based Deep Adjustment and Layered Deployment Algorithm (PDLDA). The aim is to achieve higher node coverage while minimizing the number of nodes to the maximum extent possible. Through the analysis of simulation experiment results, it is found that the PDLDA deployment algorithm, compared to other algorithms, can achieve a more uniform node distribution, improve coverage, significantly enhance network reliability, and effectively prolong the network's lifespan.