Dynamic Deployment of Mobile Sensor Nodes to Achieve Target Coverage

Abstract

Target coverage is an essential function in wireless sensor networks (WSNs), especially in applications like surveillance, environmental monitoring, and disaster response. When mobile sensor nodes are randomly deployed, achieving efficient and uniform target coverage is challenging due to limited mobility, energy constraints, and uneven distribution. This study presents a hybrid optimization approach that integrates the Virtual Force approach (VFA) with Particle Swarm Optimization (PSO) to dynamically position mobile sensor nodes for optimal target coverage with the objective of maximizing coverage and minimizing movement. The VFA is used to benefit from local interactions between nodes and guide early movement using attractive and repulsive virtual forces, facilitating rapid dispersion and preliminary coverage. We then use Particle Swarm Optimization (PSO) to globally optimize node placements, enhancing coverage quality and reducing redundant overlaps and movement expenses. The effectiveness of the proposed VFA+PSO hybrid algorithm is assessed based on two primary metrics: coverage quality, which is defined by the number of sensors observing each target, and convergence rate, demonstrated through the iterations necessary to achieve a steady state. Results from the simulation validate the effectiveness of the proposed method using different deployment scenarios of sensors by achieving better coverage more quickly and with less movement of sensors, making it perfect for changing wireless sensor network applications that require flexible and energy-saving deployment strategies.