Research On Coverage Enhancement Algorithm For Directional Sensor Networks

In the study of wireless sensor networks(WSNs),coverage problem is a foundation of every surveillance task.Different from omnidirectional sensor,the perceptive ability of directional sensor is restricted by field of view,which made the coverage problem complicated.In this paper,aiming at area coverage problem in directional sensor networks,we introduced an improved directional sensor model and proposed a coverage enhancement algorithm to obtain a high coverage.First of all,we studied and analyzed a lot about sensing model of sensor which composed directional sensor networks,and introduced a multi-detecting point sensor model and proposed a coverage enhancement algorithm based on this new model.The attractive force and the repulsive force are redefined under new sensing model.The sensing angle of each node turns to appropriate direction by the force calculation,then the overlapped area can be reduced and area coverage ratio increased.Secondly,we aware that only apply the virtual force to enhance the coverage is limited the searching performance,so we consider particle swarm algorithm(PSO),which are good at convergence speed and searching ability,to providing desirable surveillance level.We proposed a multi-detecting point based on virtual force-directed particle swarm optimization algorithm(MDPVF-PSO)and simulation results show the effectiveness of our proposed algorithm.Finally,aiming at area coverage problem in mobile directional sensor networks,we proposed a particle swarm optimization algorithm for coverage enhancement,and simulation results verify the outstanding performance of our algorithm.