Virtual force-directed particle swarm optimization for dynamic deployment in wireless sensor networks

Abstract

Dynamic deployment is one of the key topics addressed in wireless sensor networks (WSNs) study, which refers to coverage and detection probability of WSNs. This paper proposes a self-organizing algorithm for enhancing the coverage and detection probability for WSNs which consist of mobile and stationary nodes, which is so-called virtual force-directed particle swarm optimization (VFPSO). The proposed algorithm combines the virtual force (VF) algorithm with particle swarm optimization (PSO), where VF uses a judicious combination of attractive and repulsive forces to determine virtual motion paths and the rate of movement for sensors and PSO is suitable for solving multi-dimension function optimization in continuous space. In VFPSO, the velocity of each particle is updated according to not only the historical local and global optimal solutions but also the virtual forces of sensor nodes. Simulation results demonstrate that the proposed VFPSO has better performance on regional convergence and global searching than PSO algorithm and can implement dynamic deployment of WSNs more efficiently and rapidly. © Springer-Verlag Berlin Heidelberg 2007.