A multi-detecting point based on virtual force-directed particle swarm optimization algorithm for coverage enhancement in directional sensor networks
Xuan Ma, Jingyan Kang · 2018
Area coverage is the most essential issue in directional sensor networks (DSNs), which reflects the quality of service (QoS) of sensing in monitor area. Aiming at maximizing the coverage ratio of area, we introduced a multi-detecting point model, and proposed a multi-detecting point based on virtual force algorithm (MDPVF), in which the new model under virtual force makes each sensor away move from the overlapped region to the uncovered region, so that coverage holes can be reduced and coverage ratio is increased rapidly. And we proposed a multi-detecting point based on virtual force-directed particle swarm optimization algorithm (MDPVF-PSO), where the particles are updated not only according to optimal solutions of population and individual, but also virtual force from neighboring sensors and multi-detecting points. Simulation results show the effectiveness of our proposed algorithm.