Coverage in wireless sensor networks based on individual particle optimization

Effective sensor coverage is one of the key topics addressed in wireless sensor networks (WSNs) study, which refers to the deployment and detection probability of WSNs. This paper proposes a novel deployment algorithm for mobile sensor networks, based on individual particle optimization (IPO). The algorithm is designed for real-time online deployment for the purpose of maximum coverage in the environment. The mobile nodes will relocate themselves to find the best deployment under various kinds of situations in order to cover the largest area. The new locations of the mobile nodes are determined by IPO. Here, the remarkable point is the capability to be applied in a real-time manner due to considerable higher convergence rate of IPO algorithm. The experimental results verify that the deployment of the mobile sensors with IPO outperforms the previous deployment algorithms such as GA and PSO based approaches with respect to effective coverage area and computation time.