A New Approach for Area Coverage Problem in Wireless Sensor Networks with Hybrid Particle Swarm Optimization and Differential Evolution Algorithms

One of the most important and basic problems in Wireless Sensor Networks (WSNs) is the coverage problem. The coverage problem in WSNs causes the security environments is supervised by the existing sensors in the networks suitably. The importance of coverage in WSNs is so important that is one of the quality of service parameters. If the sensors do not suitably cover the physical environments they will not be enough efficient n supervision and controlling. The coverage in WSNs must be in a way that the energy of the sensors would be the least to increase the lifetime of the network. The other reasons which had increase the importance of the problem are the topologic changes of the network which are done by the damage or deletion of some of the sensors and in some cases the network must not lose its coverage. SO, in this paper we have hybrid the Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms which are the Meta-Heuristic algorithms and have analyzed the area coverage problem in WSNs. Also a PSO algorithm is implemented to compare the efficiency of the hybrid model in the same situation. The results of the experiments show that the hybrid algorithm has made more increase in the lifetime of the network and more optimized use of the energy of the sensors by optimizing the coverage of the sensors in comparison to PSO.