Dynamic cluster member selection method for multi-target tracking in wireless sensor network

Multi-target tracking (MTT) is a research hotspot of wireless sensor networks at present. A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a special cluster member (CM) node selection method is put forward in the scheme. An energy efficiency model was proposed under consideration of both energy consumption and remaining energy balance in the network. A tracking accuracy model based on area-sum principle was also presented through analyzing the localization accuracy of triangulation. Then, the two models mentioned above were combined to establish dynamic cluster member selection model for MTT where a comprehensive performance index function was designed to guide the CM node selection. This selection was fulfilled using genetic algorithm. Simulation results show that this method keeps both energy efficiency and tracking quality in optimal state, and also indicate the validity of genetic algorithm in implementing CM node selection.