Energy-efficient Optimization of Reorganization-Enabled Wireless Sensor Networks.

摘要: This paper studies the target tracking problem in wireless sensor networkswhere nodes are deployed randomly. To achieve accuracy constrained byenergy consumption, an energy-efficient optimization approach that enablesreorganization of networks is proposed. The includes threephases which related to prediction, localization and recovery, respectively. A particlefilter algorithm implemented on sink node forecast future movement thetarget first prediction phase. Upon completion this phase, most energyefficient awakened collaboratively locate target. Energy efficiencyis evaluated by ratio mutual information energy consumption. recoveryphase needed improve robustness approach. It performed when missed because incorrect predicted location. In order recapture awakening additional as few possible, a genetic-algorithm-basedmechanism introduced cover recovery area. We show proposed approachhas excellent performance. Moreover, it can efficiently reduce energyconsumption, prolong network lifetime overheads.