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.
Highlights
To reduce traffic load of the network, a data compressing based target tracking protocol is proposed in this work
Target tracking is an important problem of wireless sensor networks (WSNs)
We present a data compressing based target tracking protocol, which incorporates data approximation algorithm in the procedure of targets tracking
Summary
Target tracking is an important problem of wireless sensor networks (WSNs). It has been applied in various areas such as disaster predication, emergency response, battlefield surveillance, home and office control, etc. In the applications of target tracking with WSNs, the users are often interested in observing where the target is at each time interval and figuring its trajectory. In such cases, continuous information reporting of the target is required. The limits of WSNs including limited bandwidth, processing capabilities and energy supply challenge the research of target tracking
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