Energy-Efficient Node Selection for Target Tracking in Wireless Sensor Networks

Abstract

Saving energy while preserving accuracy is of paramount importance to target tracking in wireless sensor networks. This paper presents an energy-efficient selection of cooperative nodes. In the proposed method, the target detection probability is estimated by single-node processing based on particle filter. Then, an objective function for collaborative target tracking in wireless sensor networks is constructed according to the information utility and the remaining energy of sensor nodes. With this understanding, a dynamic node selection scheme based on genetic algorithms is proposed, which can optimize the tradeoff between the accuracy of tracking and the energy cost of nodes. Simulations demonstrate its superior performance in estimating the target location and saving sensor nodes energy.