Peer-to-Peer Collaborative Signal Processing for Target Tracking in Wireless Sensor Networks

Abstract

A distributed dynamic collaboration approach built in peer-to-peer (P2P) architecture is presented to acquire, transmit and process information in wireless sensor networks (WSNs). Several practically feasible measures of energy consumption and information utility was introduced in collaborative signal processing (CSP) for nodes selection. Then we introduce a target tracking method and present a simple but robust algorithm to integrate the results from multiple nodes. Furthermore, we introduce a progressive fusion tracking strategy based on P2P collaborative signal processing (P2P-CSP) mechanism. Finally, we illustrate an indoor tracking experiment, as well as compare the energy consumption and time delay of P2P- CSP and client/server mechanism. Experimental results verify that the proposed algorithm is a scalable, progressive, energy-efficient and robust way for target tracking