Directional The Sensor Network Coverage Enhancement Algorithm Base On Particle Swarm Optimization

With the wide application of the sensor network, a lot of problems emerged, in which coverage problem is an important problem in the sensor network. As many scholars studied this problem, different solutions were put forward, such as genetic algorithm, the greedy algorithm and the particle swarm optimization algorithm, and so on.Different schemes have different advantages.The directional sensor network is a form of wireless sensor network, this paper uses particle swarm optimization algorithm to solve the directional sensor network coverage problem, this paper includes two parts:1. The particle swarm optimization algorithm based on the displacement and the direction. This algorithm not only adjusts direction of perception of sensor nodes, but also moves the position of nodes. After making simulation of this algorithm, and comparing with the original particle swarm optimization algorithm(PSO). Experiments prove that the particle swarm optimization algorithm based on the displacement and the direction is better than the particle swarm optimization algorithm in coverage.2. The particle swarm coverage enhancement algorithm based on overlapping coverage. This algorithm gets a group optimal solution about perceived direction from the PSO,then traversing the sensor nodes, regulating the direction of a node that has overlapping sensing area, as this way to interfere with the group optimal solution to make it deviate from the local optimum particle groups. When the network need to get multiple coverage condition, k-coverage can show multiple coverage results. In this paper, the simulation results from the perspectives ofk-coverage, radius of perception, perception and the difference of the nodes’ quantity compared with the two kinds of existing algorithms, reflect the advantage of the algorithm proposed in this paper.