Wireless multihoming modeled as a multi-WLAN game

Subscribe (Full Service)


	Search: The ACM Digital Library The Guide

	Feedback

Wireless multihoming modeled as a multi-WLAN game

Full text

Pdf (632 KB)

Source

International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems archive
Proceedings of the 12th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems table of contents

Tenerife, Canary Islands, Spain

SESSION: Game-theory table of contents

Pages 147-154

Year of Publication: 2009

ISBN:978-1-60558-616-8

Author

Jerzy Konorski

Gdansk University of Technology, Gdansk, Poland

Sponsor

SIGSIM: ACM Special Interest Group on Simulation and Modeling

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 3, Downloads (12 Months): 3, Citation Count: 0

Additional Information:

abstract references index terms

Tools and Actions:	Request Permissions Review this Article Save this Article to a Binder Display Formats: BibTeX EndNote ACM Ref

DOI Bookmark:	Use this link to bookmark this Article: http://doi.acm.org/10.1145/1641804.1641831 What is a DOI?

ABSTRACT

Autonomous wireless multihomed stations (connected to multiple wireless networks) are likely to behave selfishly, trying at the same time to avoid crowded networks, select networks of higher data rates, and use the selected network in a more persistent way than standard MAC protocols prescribe. We analyze the underlying noncooperative game and find its Nash equilibria unsatisfactory. Yet for a repeated version of the game, a strategy of toggling between selfish and honest play can be devised, leading to all stations playing honest and resilient to sophisticated deviations that may seek an unfairly high bandwidth share. Numerical illustration is provided using a multi-WLAN model with each WLAN employing IEEE 802.11 MAC with a different data rate.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Berlemann, L., Hiertz, G. R., Walke, B. H., and Mangold, S. 2005. Radio resource sharing games: enabling QoS support in unlicensed bands, IEEE Network 19, 4 (July/August 2005), 59--65.
	2	Bianchi, G. 2000. Performance analysis of the IEEE 802.11 Distributed Coordination Function, IEEE J. on Selected Areas in Commun. 18, 3 (Mar. 2000), 535--547.
	3	Challet, D. and Zhang, Y.-C. 1997. Emergence of cooperation and organization in an evolutionary game. Physica A. 246 (1997), 407.
	4	Douceur, J. 2002. The Sybil attack. In Proceedings of the 1st International Workshop on P2P Systems (Cambridge MA, March 7-8, 2002).
	5	Fan Wu, Sheng Zhong, and Chunming Qiao. 2008. Globally optimal channel assignment for non-cooperative wireless networks. In Proceedings of IEEE INFOCOM 2008 (Phoenix AZ, April 13-18, 2008), 1543--1551.
	6	Friedman, E. J. and Shenker, S. 1996. Synchronous and asynchronous learning by responsive learning automata. Mimeo (1996).
	7	Fudenberg, D. and Levine, D. K. 1998. The Theory of Learning in Games. MIT Press.
	8	Fudenberg, D. and Tirole, J. 1991. Game Theory. MIT Press.
	9	Konorski, J. 2006. An Idea Bag strategy to discourage selfish behavior under Random Token MAC protocols for wireless LANs. LNCS, 4308 (2006), Springer-Verlag, 582--593.
	10	Konorski, J. 2007. A station strategy to deter backoff attacks in IEEE 802.11 LANs. J. Discr. Algor., 5,3 (2007), 436--454.
	11	Jun, C., Naixue, X., Yang, L. T., and Hed, Y. 2008. A joint selfish routing and channel assignment game in wireless mesh networks. Computer Comm., 31 (2008), 1447--1459.
	12	Konorski, 2006. J. A game-theoretic study of CSMA/CA under a backoff attack. IEEE/ACM Trans. on Networking, 14, 6 (Dec. 2006), 1167--1178.
	13	Neel, J. 2006. Analysis and design of cognitive radio networks and distributed radio resource management algorithms. Doctoral Thesis. Sept. 2006, Virginia Polytechnic Institute and State Univ., Blacksburg VA.
	14	Niyato, D. and Hossain, E. 2008. Modeling user churning behavior in wireless networks using evolutionary game theory. In Proceedings of the Wireless Communications and Networking Conference WCNC 2008 (Las Vegas, Mar. 31-Apr. 3, 2008), 2793--2797.
	15	Song, Q. and Jamalipour, A. 2005. A network selection mechanism for next generation networks. In Proceedings of IEEE International Conference on Communications ICC'05 (Seoul, Korea, May 16-20, 2005), 1418--1422.
	16	Tan, C. K., Sim, M. L., and Chuah, T. C. 2008. Game theoretic approach for channel assignment and power control with no-internal-regret learning in wireless ad hoc networks. IET Comm. 2, 9 (2008), 1159--1169.