Abstract
In this paper, the problem of collaborative tracking of mobile nodes in wireless sensor networks is addressed. Aiming at an energy efficient solution, we propose a strategy of combining target tracking with node selection procedures in order to select informative sensors to minimize the energy consumption of the tracking task using the energy model by Heinzelman, 2000. We layout a cluster-based architecture to address the limitations in computational, battery power and communications of the sensor devices. The node selection problem is formulated as a cross-layer optimization problem that is solved using a greedy algorithm. To track mobile nodes two particle filters are used: the bootstrap particle filter and the unscented particle filter, both in the centralized and in the distributed manner. Their performance are compared with the distributed sigma-point information filter in literature, under two common channel models: the log-normal shadowing and the Rayleigh fading.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless Sensor Networks: A Survey. Computer Networks (Elsevier), 393–422 (March 2002)
Ihler, A.T., et al.: Nonparametric belief propagation for self-localization of sensor networks. IEEE Journal on Selected Areas in Communications 23(4) (April 2005)
Lee, J., Cho, K., Lee, S., Kwon, T., Choi, Y.: Distributed and energy-efficient target localization and tracking in wireless sensor netwoks. Computer Communications 29, 2494–2505 (2006)
Vercauteren, T., Wang, X.: Decentralized Sigma-Point Information Filters for Target Tracking in Collaborative Sensor Networks. IEEE Transactions on Signal Processing 53(8) (August 2005)
Oshman, Y., Davidson, P.: Optimization of observer trajectories for bearings-only target localization. IEEE Transactions on Aerospace and Electronic Systems 35, 892–902 (1999)
Ertin, E., Fisher, J.W., Potter, L.C.: Maximum Mutual Information Principle for Dynamic Sensor Query Problems. In: Zhao, F., Guibas, L.J. (eds.) IPSN 2003. LNCS, vol. 2634, pp. 405–416. Springer, Heidelberg (2003)
Wang, H., Pottie, G., Yao, K., Estrin, D.: Entropy-based Sensor Selection Heuristic for Target Localization. In: International Workshop on Information Processing in Sensor Networks (IPSN), Berkeley, California, April 26-27 (2004)
Kaplan, L.M.: Global node selection for localization in a distributed sensor network. IEEE Transactions on Aerospace and Electronics Systems 42(1), 113–135 (2006)
Kaplan, L.M.: Local node selection for localization in a distributed sensor network. IEEE Transactions on Aerospace and Electronics Systems 42(1), 136–146 (2006)
Wang, Q., Chen, W.-P., Zheng, R., Lee, K., Sha, L.: Acoustic Target Tracking Using Tiny Wireless Sensor Devices. In: Zhao, F., Guibas, L.J. (eds.) IPSN 2003. LNCS, vol. 2634, pp. 642–657. Springer, Heidelberg (2003)
Chen, W.-P., Hou, J.C., Sha, L.: Dynamic Clustering for Acoustic Target Tracking in Wireless Sensor Networks. IEEE Trans. on Mobile Computing 3(3), 258–271 (2004)
Kung, H.T., Vlah, D.: Efficient Location Tracking Using Sensor Networks. In: WCNC (March 2003)
Lin, C.-Y., Tseng, Y.-C.: Structures for In-Network Moving Object Tracking in Wireless Sensor Networks. In: BROADNETS (2004)
Zhang, W., Cao, G.: DCTC: Dynamic Convoy Tree-Based Collaboration for Target Tracking in Sensor Networks. IEEE Trans. on Wireless Communications (2004)
Liu, J., Reich, J., Zhao, F.: Collaborative in-network processing for target tracking. EURASIP, J. Appl. Signal Processing, 378–391 (2003)
Zhao, F., Shin, J., Reich, J.: Information-driven dynamic sensor collaboration for tracking applications. IEEE Signal Processing Magazine 19(2), 61–72 (2002)
Kreucher, C.M., Hero, A.O., Kastella, K.D., Morelande, M.R.: An Information-Based Approach to sensor Management in Large Dynamic Networks. Proceeding of IEEE 95, 978–999 (2007)
Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H.: Energy-Efficient Communication Protocol for Wireless Microsensor Networks. In: Proceedings of 33rd Hawaii International Conference on System Sciences (HICSS 2000), Maui, Hawaii (January 2000)
Rappaport, T.S.: Wireless Communications. Principles and Practice, 2nd edn. Prentice Hall, Englewood Cliffs
Doucet, A., de Freitas, N., Gordon, N.: Sequential monte carlo methods in practice. Springer, Heidelberg (2001)
Gordon, N.J., Salmond, D.J., Smith, A.F.M.: Novel approach to nonlinear/nonlinear gaussian bayesian state estimation. IEEE Proceedings-F 140(2), 107–113 (1993)
Van der Merwe, R., Doucet, A., de Freitas, N., Wan, E.: The Unscented Particle Filter. In: NIPS, pp. 584–590 (2000)
Guo, D., Wang, X.: Dynamic sensor collaboration via sequential monte carlo. IEEE JSAC 22(6), 1037–1047 (2004)
Arienzo, L., Longo, M.: Energy-Efficient Tracking Strategy for Wireless Sensor Networks. In: Proceedings of IEEE MASS 2008, Workshop on Localized Communication and Topology Protocols for Ad hoc Networks, Atlanta, Georgia (September 2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Arienzo, L., Longo, M. (2010). Energy-Efficient Target Tracking in Sensor Networks. In: Zheng, J., Simplot-Ryl, D., Leung, V.C.M. (eds) Ad Hoc Networks. ADHOCNETS 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 49. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17994-5_17
Download citation
DOI: https://doi.org/10.1007/978-3-642-17994-5_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17993-8
Online ISBN: 978-3-642-17994-5
eBook Packages: Computer ScienceComputer Science (R0)