A tight characterization of strategic games with a unique equlibrium

Antoniy Ganchev, Lata Narayanan, Sunil Shende

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Media access protocols in wireless networks require each contending node to wait for a backoff time chosen randomly from a fixed range, before attempting to transmit on a shared channel. However, nodes acting in their own selfish interest may not follow the protocol. In this paper, we use a game-theoretic approach to study how nodes might be induced to adhere to the protocol. In particular, a static version of the problem is modeled as a strategic game played by noncooperating, rational players (the nodes). A strategy for a player corresponds to a backoff value in the medium access protocol. We are interested in designing a game which exhibits a unique Nash equilibrium corresponding to a pre-specified full-support distribution profile. In the context of the media access problem, the equilibrium of the game would correspond to nodes following the protocol, viz. choosing backoff times randomly from a given range of values according to the prespecified distribution. Building on results described in earlier work, we identify the exact relationship that must hold between the cardinalities of the players' action sets that would make it possible to design such a game.

Original languageEnglish (US)
Title of host publicationProceedings of the 2009 International Conference on Game Theory for Networks, GameNets '09
Pages366-373
Number of pages8
DOIs
StatePublished - 2009
Event2009 International Conference on Game Theory for Networks, GameNets '09 - Istanbul, Turkey
Duration: May 13 2009May 15 2009

Publication series

NameProceedings of the 2009 International Conference on Game Theory for Networks, GameNets '09

Other

Other2009 International Conference on Game Theory for Networks, GameNets '09
Country/TerritoryTurkey
CityIstanbul
Period5/13/095/15/09

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition

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