An Energy-Efficient Object Tracking Algorithm in Sensor Networks

Object tracking needs to meet certain real-time and precision constraints, while limited power and storage of sensors issue challenges for it. This paper proposes an energy efficient tracking algorithm (EETA) that reduces energy consumption in sensor network by introducing an event-driven sleep scheduling mechanism. EETAgives tradeoffs between real time and energy efficiency by making a maximum number of sensor nodes outside tracing area stay asleep. EETAreduces the computation complexity on sensors to O(N)by formulating the location predication of an object as a state estimation problem of sensor node, instead of building a complex model of its trajectory.EETAlocates the object using modified weighted centroid algorithm with the complexity of O(N). We evaluate our method with a network of 64 sensor nodes, as well as an analytical probabilistic model. The analytical and experimental results demonstrate the effectiveness of proposed methods.

[1]  Akbar M. Sayeed,et al.  Detection, Classification and Tracking of Targets in Distributed Sensor Networks , 2002 .

[2]  Akbar M. Sayeed,et al.  Collaborative Signal Processing for Distributed Classification in Sensor Networks , 2003, IPSN.

[3]  Jeung-Yoon Choi,et al.  On target tracking with binary proximity sensors , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[4]  Gang Zhou,et al.  Achieving Long-Term Surveillance in VigilNet , 2006, INFOCOM.

[5]  Yanghee Choi,et al.  Distributed and energy-efficient target localization and tracking in wireless sensor networks , 2006, Comput. Commun..

[6]  Feng Zhao,et al.  Information-Driven Dynamic Sensor Collaboration for Tracking Applications , 2002 .

[7]  D. McErlean,et al.  Distributed detection and tracking in sensor networks , 2002, Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002..

[8]  Guohong Cao,et al.  DCTC: dynamic convoy tree-based collaboration for target tracking in sensor networks , 2004, IEEE Transactions on Wireless Communications.

[9]  Jaehoon Jeong,et al.  MCTA: Target Tracking Algorithm Based on Minimal Contour in Wireless Sensor Networks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[10]  Yu Hen Hu,et al.  Detection, classification, and tracking of targets , 2002, IEEE Signal Process. Mag..

[11]  S. Shankar Sastry,et al.  Tracking on a graph , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[12]  Gang Zhou,et al.  Achieving Real-Time Target Tracking UsingWireless Sensor Networks , 2006, 12th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'06).