Multiple Mobile Target Tracking in Wireless Sensor Networks

  • Charly Lersteau
  • Marc Sevaux
  • André Rossi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8472)


An object tracking sensor network (OTSN) is made of \(m\) static wireless sensors scattered throughout a geographical area for tracking \(n\) mobile targets. Assuming that sensors have non-rechargeable batteries, one of the most critical aspects of OTSN is energy consumption. In this paper, we propose linear programming models which handle two missions : monitoring and reporting data to a base station, and two distinct problems : minimize energy consumption and maximize network lifetime. We suppose that trajectories of targets are known and targets should be monitored by sensors. To reach our goals, we schedule the active and sleep states of the sensors and route the data to a base station while keeping track of the targets. To solve our problems, we process a temporal discretization according to the intersection points between the trajectories and the sensing ranges of the sensors. The obtained sets of sensors for each time window help us to create linear programming models. These basic problems offer perspectives in performance evaluation of energy-conservation protocols and distributed algorithms in wireless sensor networks.


Multiple target tracking Wireless sensor networks Lifetime maximization Energy consumption minimization 


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  1. Berman, P., Calinescu, G., Shah, C., Zelikovsky, A.: Power efficient monitoring management in sensor networks. In: 2004 IEEE Wireless Communications and Networking Conference, WCNC, vol. 4, pp. 2329–2334. IEEE (2004)Google Scholar
  2. Lin, F.Y.-S., Lee, C.-T.: An efficient lagrangean relaxation-based object tracking algorithm in wireless sensor networks. Sensors 10(9), 8101–8118 (2010)CrossRefGoogle Scholar
  3. Liu, H., Chu, X., Leung, Y.-W., Jia, X., Wan, P.-J.: Maximizing lifetime of sensor-target surveillance in wireless sensor networks. In: IEEE Global Telecommunications Conference, GLOBECOM 2009, pp. 1–6. IEEE (2009)Google Scholar
  4. Liu, H., Chu, X., Leung, Y.-W., Jia, X., Wan, P.-J.: General maximal lifetime sensor-target surveillance problem and its solution. IEEE Transactions on Parallel and Distributed Systems 22(10), 1757–1765 (2011)CrossRefGoogle Scholar
  5. Naderan, M., Dehghan, M., Pedram, H., Hakami, V.: Survey of mobile object tracking protocols in wireless sensor networks: a network-centric perspective. International Journal of Ad Hoc and Ubiquitous Computing 11(1), 34–63 (2012)CrossRefGoogle Scholar
  6. Naderan, M., Dehghan, M., Pedram, H.: Primal and dual-based algorithms for sensing range adjustment in wsns. The Journal of Supercomputing, 1–21 (2013)Google Scholar
  7. Ramya, K., Praveen Kumar, K., Srinivas Rao, V.: A survey on target tracking techniques in wireless sensor networks. International Journal of Computer Science and Engineering Survey 3(4) (2012)Google Scholar
  8. Rossi, A., Singh, A., Sevaux, M.: Column generation algorithm for sensor coverage scheduling under bandwidth constraints. Networks 60(3), 141–154 (2012)CrossRefzbMATHMathSciNetGoogle Scholar
  9. Slijepcevic, S., Potkonjak, M.: Power efficient organization of wireless sensor networks. In: IEEE International Conference on Communications, ICC 2001, vol. 2, pp. 472–476. IEEE (2001)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Lab-STICC Centre de rechercheUniversité de Bretagne-SudLorient cedexFrance

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