Compressing Information of Target Tracking in Wireless Sensor Networks

Abstract

Target tracking is a well studied topic in wireless sensor networks. It is a procedure that nodes in the network collaborate in detecting targets and transmitting their information to the base-station continuously, which leads to data implosion and redundancy. To reduce traffic load of the network, a data compressing based target tracking protocol is proposed in this work. It first incorporates a clustering based data gather method to group sensor nodes into clusters. Then a novel threshold technique with bounded error is proposed to exploit the spatial correlation of sensed data and compress the data in the same cluster. Finally, the compact data presentations are transmitted to the base-station for targets localization. We evaluate our approach with a comprehensive set of simulations. It can be concluded that the proposed method yields excellent performance in energy savings and tracking quality.