Advertisement

No Regret Learning for Sensor Relocation in Mobile Sensor Networks

  • Jin Li
  • Chi Zhang
  • Wei Yi Liu
  • Kun Yue
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7030)

Abstract

Sensor relocation is a critical issue because it affects the coverage quality and capability of a mobile sensor network. In this paper, the problem of sensor relocation is formulated as a repeated multi-player game. At each step of repeated interactions, each node uses a distributed no-regret algorithm to optimize its own coverage while minimizing the locomotion energy consumption. We prove that if all nodes adhere to this algorithm to play the game, collective behavior converges to a pure Nash equilibrium. Simulation results show that a good coverage performance can be obtained when a pure Nash equilibrium is achieved.

Keywords

mobile sensor networks sensor relocation repeated game pure Nash equilibria no-regret learning 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Younisa, M., Akkaya, K.: Strategies and techniques for node placement in wireless sensor networks: A survey. Journal Ad Hoc Networks Archive 6(4) (June 2008)Google Scholar
  2. 2.
    Bartolini, N., Calamoneri, T., La Porta, T., Massini, A., Silvestri, S.: Autonomous deployment of heterogeneous mobile sensors. In: ICNP 2009, pp. 42–51 (2009)Google Scholar
  3. 3.
    Ghosh, A., Das, S.K.: Coverage and connectivity issues in wireless sensor networks: A survey. Pervasive and Mobile Computing 4(3), 303–334 (2008)CrossRefGoogle Scholar
  4. 4.
    Bartolini, N., Calamoneri, T., La Porta, T.F., Silvestri, S.: Mobile Sensor Deployment in Unknown Fields. In: INFOCOM 2010, pp. 471–475 (2010)Google Scholar
  5. 5.
    Wang, G., Irwin, M.J., Fu, H., Berman, P., Zhang, W., La Porta, T.: Optimizing sensor movement planning for energy efficiency. TOSN 7(4), 33 (2011)CrossRefGoogle Scholar
  6. 6.
    Meguerdichian, S., Koushanfar, F., Potkonjak, M., Srivastava, M.B.: Coverage Problems in Wireless Ad-hoc Sensor Networks. IEEE INFOCOM 3, 1380–1387 (2001)Google Scholar
  7. 7.
    Marden, J.R., Wierman, A.: Distributed welfare games with applications to sensor coverage. In: Proc. CDC, pp. 1708–1713 (2008)Google Scholar
  8. 8.
    Bai, X., Yun, Z., Xuan, D., Chen, B., Zhao, W.: Optimal Multiple-Coverage of Sensor Networks. In: Proc. of IEEE International Conference on Computer Communications (INFOCOM) (to appear, April 2011)Google Scholar
  9. 9.
    Wang, G., Cao, G., La Porta, T.F., Zhang, W.: Sensor relocation in mobile sensor networks. In: INFOCOM 2005, pp. 2302–2312 (2005)Google Scholar
  10. 10.
    Monderer, D., Shapley, L.S.: Potential games. Games and Economic Behavior 14, 124–143 (1996)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Banerjee, B., Peng, J.: Efficient No-Regret Multiagent Learning. In: AAAI 2005, pp. 41–46 (2005)Google Scholar
  12. 12.
    Greenwald, A., Jafari, A.: A General Class of No-Regret Algorithms and Game-Theoretic Equilibria. In: Proceedings of the 2003 Computational Learning Theory Conference, pp. 1–11 (August 2003)Google Scholar
  13. 13.
    Nash, J.F.: Equilibrium points in n-person games. Proc. of National Academy of Sciences 36, 48–49 (1950)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Fudenberg, D., Tirole, J.: Game Theory. MIT Press (1991)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jin Li
    • 1
    • 2
    • 3
  • Chi Zhang
    • 2
  • Wei Yi Liu
    • 1
  • Kun Yue
    • 1
  1. 1.School of Information ScienceYunnan UniversityKunmingChina
  2. 2.School of SoftwareYunnan UniversityKunmingChina
  3. 3.Key laboratory in Software EngineeringKunmingChina

Personalised recommendations