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A game theoretical approach to clustering of ad-hoc and sensor networks

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Abstract

Game theory has been used for decades in fields of science such as economics and biology, but recently it was used to model routing and packet forwarding in wireless ad-hoc and sensor networks. However, the clustering problem, related to self-organization of nodes into large groups, has not been studied under this framework. In this work our objective is to provide a game theoretical modeling of clustering for ad-hoc and sensor networks. The analysis is based on a non-cooperative game approach where each sensor behaves selfishly in order to conserve its energy and thus maximize its lifespan. We prove the Nash Equilibria of the game for pure and mixed strategies, the expected payoffs and the price of anarchy corresponding to these equilibria. Then, we use this analysis to formulate a clustering mechanism (which we called Clustered Routing for Selfish Sensors—CROSS), that can be applied to sensor networks in practice. Comparing this mechanism to a popular clustering technique, we show via simulations that CROSS achieves a performance similar to that of a very popular clustering algorithm.

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References

  1. Agah, A., Das, S. K., & Basu, K. (2004). A game theory based approach for security in wireless sensor networks. In Proceedings of the IEEE international conference on performance, computing and communications (IPCCC 2004), Phoenix, Arizona, April 15–17, 2004.

  2. Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: a survey. Computer Networks, 38(4), 393–422.

    Article  Google Scholar 

  3. Altman, E., Boulogne, T., Azouzi, R. E., Jimenez, T., & Wynter, L. (2006). A survey on networking games in telecommunications. Computers and Operations Research, 33(2), 286–311.

    Article  Google Scholar 

  4. Altman, E., Kherani, A. A., Michiardi, P., & Molva, R. (2005). Non-cooperative forwarding in ad-hoc networks. In Lecture notes on computer science (Vol. 3462/2005, pp. 486–498). Berlin: Springer.

    Google Scholar 

  5. Chatterjee, M., Das, S. K., & Turgut, D. (2002). WCA: a weighted clustering algorithm for mobile ad hoc networks. Cluster Computing, 5(2), 193–204.

    Article  Google Scholar 

  6. Felegyhazi, M., Hubaux, J. P., & Buttyan, L. (2003). Equilibrium analysis of packet forwarding strategies in wireless ad hoc networks—the dynamic case (Tech. rep.).

  7. Felegyhazi, M., Hubaux, J. P., & Buttyan, L. (2006). Nash equilibria of packet forwarding strategies in wireless ad hoc networks. IEEE Transactions on Mobile Computing, 5(5), 463–476.

    Article  Google Scholar 

  8. Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(5), 660–670.

    Article  Google Scholar 

  9. Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of 33rd annual Hawaii international conference on system sciences (HICSS), Maui, Hawaii, USA, January 4–7, 2000.

  10. Michiardi, P., & Molva, R. (2004). Analysis of cooperation strategies in mobile ad hoc networks with imperfect monitoring (Research Report RR-04-099). Institut Eurecom, Sophia-Antipolis.

  11. Muruganathan, S. D., Ma, D. C., Bhasin, R. I., & Fapojuwo, A. O. (2005). A centralized energy-efficient routing protocol for wireless sensor networks. IEEE Communications Magazine, 43(3), S8–S13.

    Article  Google Scholar 

  12. Nurmi, P. (2004). Modelling routing in wireless ad hoc networks with dynamic Bayesian games. In Proc. of 1st annual IEEE communications society conference on sensor and ad hoc communications and networks (SECON 2004) (pp. 63–70). Santa Clara, CA, USA.

  13. Osborne, M. J. (2004). An introduction to game theory. London: Oxford University Press.

    Google Scholar 

  14. Srivastava, V., Neel, J., MacKenzie, A. B., Menon, R., DaSilva, L. A., Hicks, J. E., Reed, J. H., & Gilles, R. P. (2005). Using game theory to analyze wireless ad hoc networks. IEEE Communications Surveys and Tutorials, 7(4), 46–56.

    Article  Google Scholar 

  15. von Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton: Princeton University Press.

    Google Scholar 

  16. Younis, O., & Fahmy, S. (2004). Distributed clustering in ad-hoc sensor networks a hybrid, energy-efficient approach. IEEE Transactions on Mobile Computations, 3(4), 366–379.

    Article  Google Scholar 

  17. Zeng-wei, Z., Zhao-hui, W., & Huai-zhong, L. (2004). Clustering routing algorithm for game-theoretic techniques for wsns. In Proceedings of IEEE international symposium on circuits and systems (ISCAS 2004), Vancouver, Canada, May 23–26, 2004.

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Authors and Affiliations

  1. Dept. Electrical and Computer Engineering, Aristotle University of Thessaloniki, Panepistimioupolis, 54124, Thessaloniki, Greece

    Georgios Koltsidas & Fotini-Niovi Pavlidou

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  1. Georgios Koltsidas
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  2. Fotini-Niovi Pavlidou
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Correspondence to Georgios Koltsidas.

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Koltsidas, G., Pavlidou, FN. A game theoretical approach to clustering of ad-hoc and sensor networks. Telecommun Syst 47, 81–93 (2011). https://doi.org/10.1007/s11235-010-9303-5

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  • DOI: https://doi.org/10.1007/s11235-010-9303-5

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