Research Of Wireless Sensor Networks Area Coverage Optimization Algorithm Based On Artificial Bee Colony

Area coverage is one of the hot spots of wireless sensor networks, and its main evaluation index is rate of area coverage. In order to improve the quality of network service, mobile nodes are intruded to improve the network performance, in wireless sensor network with coverage holes. Main research content of this paper is as follows:1) A centralized coverage optimization algorithm based on global guided coevolution of artificial bee colony is proposed for the problem that traditional artificial bee colony algorithm has slow convergence speed and easy falls into local optimum in centralized coverage optimization. The algorithm uses new nectar update formula and the vector segmentation technique to improve the rate of convergence, also uses the selection strategy of moved position to find the optimal position of nodes to reduce node moving distance. Simulation results show that the algorithm not only enhances the coverage optimization results and convergence speed of the algorithm, and reduces the node moving distance. So it is suitable for higher requirement of the wireless sensor network optimization on perceived quality.2) Although the centralized algorithm can effectively optimize the area coverage problem, but it cannot cope with the problem of the area coverage problem of the wireless sensor network with island phenomenon. Aimed at this problem, a distributed coverage optimization based on artificial bee colony is proposed. The algorithm uses mobile node to partition optimization area and by the local information uses artificial bee colony algorithm to optimize its own position. The simulation results show that the proposed algorithm can effectively improve the quality of the network perception, and can be used for the optimization of the wireless sensor network with the uneven distribution of nodes and the phenomenon of isolated islands.