Directional Probability Perceived Nodes Deployment Based on Particle Swarm Optimization

Node deployment is the key problem of wireless sensor network technology. For a directional sensor network, the perceived probability model reflects the quality of the network. The problem of the probability node deployment is too little of the distribution of the nodes asymmetrical. In this paper, we study the probability model of directional perceived nodes and propose an improved deterministic deployment algorithm based on particle swarm optimization to increase perceived probability. By analyzing the coverage probability of the monitoring area with different deployment models to obtain more serviceable environmental data of the monitoring areas, experimental results demonstrate that, compared with random deployment, sixteen percent is improved by the proposed algorithm.