Coordinated and Adaptive Information Collecting in Target Tracking Wireless Sensor Networks

Abstract

Energy conservation has been known as the most important issue for many applications in wireless sensor networks (WSNs). For data gathering in a clustered sensor network, most existing work focuses on fusing data at cluster heads (CHs). However, in target tracking applications, these approaches do not consider that one target is usually detected by sensor nodes in multiple clusters, which leads to redundant data transmissions from CHs to the sink so as to waste much energy. To solve it, this paper proposes a coordinated and adaptive information collecting strategy (CAICS) for target tracking in clustered WSNs. In CAICS, a coordinated node selection method considering the spatial correlation of sensing nodes is proposed to dynamically select the best set of nodes for tracking missions. Moreover, an adaptive aggregation node is selected for data collection to reduce the redundant data transmission and balance the energy cost. Experimental results demonstrate that the proposed approach reduces the computational complexity of node selections without degrading tracking accuracy and achieves a significant energy consumption reduction and network lifetime extension compared with the state-of-the-art approaches.