Dynamic cluster member selection method for multi-target tracking in wireless sensor network
来源期刊：中南大学学报(英文版)2014年第2期
论文作者：CAI Zi-xing(蔡自兴) WEN Sha(文莎) LIU Li-jue(刘丽珏)
文章页码：636 - 645
Key words：wireless sensor networks; multi-target tracking; collaborative task allocation; dynamic cluster; comprehensive performance index function
Abstract: 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.
CAI Zi-xing(蔡自兴), WEN Sha(文莎), LIU Li-jue(刘丽珏)
(School of Information Science and Engineering, Central South University, Changsha 410083, China)
Abstract: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.
Key words:wireless sensor networks; multi-target tracking; collaborative task allocation; dynamic cluster; comprehensive performance index function
