Minimal K-Covering Set Algorithm based on Particle Swarm Optimizer

For random high density distribution in wireless sensor networks in this article have serious redundancy problems. In order to maximize the cost savings network resources for wireless sensor networks, extend the life network, this paper proposed a algorithm for the minimal k-covering set based on particle swarm optimizer. Firstly, the network monitoring area is divided into a number of grid points. Utilization rate and the node minimum are used as optional objective, and a combinatorial optimization mathematical model is established. Then using Particle Swarm Optimizer to solve optimization model, thus the optimal network coverage and the utilization od sensor nodes are obtained. Simulation results that algorithm has reduced node redundancy and the energy consumption, and improved the network coverage effectively.