Advertisement

Wireless Networks

, Volume 17, Issue 2, pp 411–435 | Cite as

A non-cooperative game-theoretic approach to channel assignment in multi-channel multi-radio wireless networks

  • Rohith Dwarakanath VallamEmail author
  • Arun A. Kanagasabapathy
  • C. Siva Ram Murthy
Article

Abstract

Channel assignment in multi-channel multi-radio wireless networks poses a significant challenge due to scarcity of number of channels available in the wireless spectrum. Further, additional care has to be taken to consider the interference characteristics of the nodes in the network especially when nodes are in different collision domains. This work views the problem of channel assignment in multi-channel multi-radio networks with multiple collision domains as a non-cooperative game where the objective of the players is to maximize their individual utility by minimizing its interference. Necessary and sufficient conditions are derived for the channel assignment to be a Nash Equilibrium (NE) and efficiency of the NE is analyzed by deriving the lower bound of the price of anarchy of this game. A new fairness measure in multiple collision domain context is proposed and necessary and sufficient conditions for NE outcomes to be fair are derived. The equilibrium conditions are then applied to solve the channel assignment problem by proposing three algorithms, based on perfect/imperfect information, which rely on explicit communication between the players for arriving at an NE. A no-regret learning algorithm known as Freund and Schapire Informed algorithm, which has an additional advantage of low overhead in terms of information exchange, is proposed and its convergence to the stabilizing outcomes is studied. New performance metrics are proposed and extensive simulations are done using Matlab to obtain a thorough understanding of the performance of these algorithms on various topologies with respect to these metrics. It was observed that the algorithms proposed were able to achieve good convergence to NE resulting in efficient channel assignment strategies.

Keywords

Multi-channel multi-radio wireless networks Channel assignment Centralized and distributed algorithms Game theory 

Notes

Acknowledgments

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions. This work was supported by the Department of Science and Technology, New Delhi, India. It was carried out by Rohith Dwarakanath Vallam when he was pursuing the Master of Science (by Research) degree at the Department of Computer Science and Engineering (CSE), Indian Institute of Technology, Madras (IITM), Chennai, India. Arun A. Kanagasabapathy contributed initially to this work when he was pursuing Bachelor of Technology (B.Tech) degree at the Department of CSE, IITM.

References

  1. 1.
    IEEE 802.11b standard, standards.ieee.org/getieee802/download/802.11b-1999.pdf.Google Scholar
  2. 2.
    IEEE 802.11a standard, standards.ieee.org/getieee802/download/802.11a-1999.pdf.Google Scholar
  3. 3.
    Aardal, K. I., van Hoesel, S. P. M., Koster, A. M. C. A., Mannino, C., & Sassano, A. (2003). Models and solution techniques for frequency assignment problems. 4OR: A Quarterly Journal of Operations Research, 1(4), 261–317.zbMATHGoogle Scholar
  4. 4.
    Riihijarvi, J., Petrova, M., Mahonen, P., & de Almeida Barbosa, J. (2006). Performance evaluation of automatic channel assignment mechanism for IEEE 802.11 based on graph colouring. In Proceedings of the 17th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC ’06), September 2006, pp. 1–5.Google Scholar
  5. 5.
    Leung, K., & Kim, B.-J. (2003). Frequency assignment for IEEE 802.11 wireless networks. In Proceedings of the 58th IEEE Vehicular Technology Conference (VTC ’03), vol. 3, Oct 2003, pp. 1422–1426.Google Scholar
  6. 6.
    Mishra, A., Banerjee, S., & Arbaugh, W. (2005). Weighted coloring based channel assignment for WLANs. ACM SIGMOBILE Mobile Computing and Communications Review, 9(3), 19–31.CrossRefGoogle Scholar
  7. 7.
    Alicherry, M., Bhatia, R., & Li, L. E. (2002). Joint channel assignment and routing for throughput optimization in multi-radio wireless mesh networks. In Proceedings of the 11th International Conference on Mobile Computing and Networking (MOBICOM ’05), Aug 2002, pp. 58–72.Google Scholar
  8. 8.
    Shin, M., Lee, S., & Kim, Y. (2006). Distributed channel assignment for multi-radio wireless networks. In Proceedings of the 3rd IEEE International Conference on Mobile, Ad Hoc and Sensor Systems (MASS ’06), October 2006, pp. 417–426.Google Scholar
  9. 9.
    Li, N., Hou, J., & Sha, L. (2003). Design and analysis of an MST-based topology control algorithm. In Proceedings of the 22nd IEEE International Conference on Computer Communications (INFOCOM ’03), vol. 3, March 2003, pp. 1702–1712.Google Scholar
  10. 10.
    Das, A., Alazemi, H., Vijaykumar, R., & Roy, S. (2005). Optimization models for fixed channel assignment in wireless mesh networks with multiple radios. In Proceedings of the 2nd IEEE Communication Society Conference on Sensor and Ad Hoc Communications and Networks (SECON ’05), September 2005, pp. 463–474.Google Scholar
  11. 11.
    Cagalj, M., Ganeriwal, S., Aad, I., & Hubaux, J.-P. (2005). On selfish behaviour in CSMA/CA networks. In Proceedings of the 24th IEEE Conference on Computer Communications (INFOCOM ’05), vol. 4, March 2005, pp. 2513–2524.Google Scholar
  12. 12.
    Konorski, J. (2002). Multiple access in ad-hoc wireless LANs with noncooperative stations. In Proceedings of the 2nd International Conference on Networking of the IFIP Technical Committee on Communication Systems (TC6), May 2002, pp. 1141–1146.Google Scholar
  13. 13.
    MacKenzie A. B., & Wicker, S. B. (2003). Stability of multipacket slotted aloha with selfish users and perfect information. In Proceedings of the 22nd IEEE International Conference on Computer Communications (INFOCOM ’03), vol. 3, April 2003, pp. 1583–1590.Google Scholar
  14. 14.
    Halldorsson, M. M., Halpern, J. Y., & Li, L. E. (2004). On spectrum sharing games. In Proceedings of the 23rd Annual ACM Symposium on Principles of Distributed Computing (PODC’ 04), July 2004, pp. 107–114.Google Scholar
  15. 15.
    Wu, F., Zhong, S., & Qiao, C. (2008). Globally optimal channel assignment for non-cooperative wireless networks. In Proceedings of the 27th International IEEE Conference on Computer Communications (INFOCOM ’08), April 2008, pp. 1543–1551.Google Scholar
  16. 16.
    Nie, N., & Comaniciu, C. (2005). Adaptive channel allocation spectrum etiquette for cognitive radio networks. In Proceedings of the 1st IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN ’05), Nov 2005, pp. 269–278.Google Scholar
  17. 17.
    Felegyhazi, M., Cagalj, M., Bidokhti, S. S., & Hubaux, J.-P. (2007). Non-cooperative multi-radio channel allocation in wireless networks. In Proceedings of the 26th International IEEE Conference on Computer Communications (INFOCOM ’07), March 2007, pp. 1442–1450.Google Scholar
  18. 18.
    Gao, L., & Wang, X. (2008). A game approach for multi-channel allocation in multi-hop wireless networks. In Proceedings of the 9th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MOBIHOC ’08), May 2008, pp. 303–312.Google Scholar
  19. 19.
    Gupta, R., Musacchio, J., & Walranda, J. (2007). Sufficient rate constraints for QoS flows in ad-hoc networks. Ad Hoc Networks, vol. 5, no. 4, pp. 429–443, May 2007.CrossRefGoogle Scholar
  20. 20.
    Luo, H., Lu, S., & Bhargavan, V. (2000). A new model for packet scheduling in multihop wireless networks. In Proceedings of the 6th Annual International Conference on Mobile Computing and Networking (MOBICOM ’00), August 2000, pp. 76–86.Google Scholar
  21. 21.
    Jain, K., Padhye, J., Padmanabhan, V. N., & Qiu, L. (2003). Impact of interference on multi-hop wireless network performance. In Proceedings of the 9th Annual International Conference on Mobile Computing and Networking (MOBICOM ’03), September 2003, pp. 66–80.Google Scholar
  22. 22.
    Osborne M. J., & Rubinstein, A. (1994). A Course in Game Theory. Cambridge: MIT Press.Google Scholar
  23. 23.
    Bianchi, G. (2000). Performance analysis of the IEEE 802.11 distributed coordination function. IEEE Journal on Selected Areas in Communications, 18(3), 535–547.CrossRefGoogle Scholar
  24. 24.
    IEEE standard for wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications. (1997). P802.11.Google Scholar
  25. 25.
    Koutsoupias, E., & Papadimitriou, C. H. (1993). Worst-case equilibria. In Proceedings of the 16th Annual Conference in Theoretical Aspects of Computer Science, vol. 1563, Lecture Notes in Computer Science, 1999, pp. 404–413.Google Scholar
  26. 26.
    Auer, P., Cesa-Bianchi, N., Freund, Y., & Schapire, R. E. (1995). Gambling in a rigged casino: The adversarial multi-armed bandit problem. In Proceedings of the 36th Annual Symposium on Foundations of Computer Science (FOCS ’95), October 1995, pp. 322–331.Google Scholar
  27. 27.
    Littlestone, N., & Warmuth, M. K. (1994). The weighted majority algorithm. Information and Computation, 108(2), 212–261.zbMATHCrossRefMathSciNetGoogle Scholar
  28. 28.
    Freund, Y., & Schapire, R. (1995). A decision-theoretic generalization of on-line learning and an application to boosting. In Proceedings of the 2nd European Conference on Computational Learning Theory (EuroCOLT ’95), May 1995, pp. 23–37.Google Scholar
  29. 29.
    The Stanford GraphBase: A Platform for Combinatorial Computing, http://www-cs-faculty.stanford.edu/knuth/sgb.html.
  30. 30.
    Phillips, G., Shenker, S., & Tangmunarunkit, H. (1999). Scaling of multicast trees: Comments on the Chuang-Sirbu scaling law. In Proceedings of the ACM Annual Conference of the Special Interest Group on Data Communication (ACM SIGCOMM’99), pp. 41–51.Google Scholar
  31. 31.
    Greenwald, A., & Jafari, A. (2003). A class of no-regret algorithms and game-theoretic equilibria. In Proceedings of the 16th Annual Conference on Learning Theory (COLT 2003), August 2003, pp. 1–11.Google Scholar
  32. 32.
    Lim, J. G., Chou, C. T., & Jha, S. (2007). Non-cooperative coexistence of co-located independent wireless mesh networks. In Proceedings of the 4th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS 2007), October 2007, pp. 1–9.Google Scholar
  33. 33.
    Cesa-Bianchi, N., Lugosi, G. (2006). Prediction, Learning, and Games. Cambridge: Cambridge University Press.Google Scholar
  34. 34.
    Young, P. (2004). Strategic Learning and its limits. Oxford: Oxford University Press.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Rohith Dwarakanath Vallam
    • 1
    Email author
  • Arun A. Kanagasabapathy
    • 2
  • C. Siva Ram Murthy
    • 3
  1. 1.Indian Institute of Science (IISc)BengaluruIndia
  2. 2.Bloomberg, L.P.LondonUK
  3. 3.Department of CSEIITMChennaiIndia

Personalised recommendations