A rate-adaptive MAC protocol for multi-Hop wireless networks
Proceedings of the 7th annual international conference on Mobile computing and networking
Opportunistic media access for multirate ad hoc networks
Proceedings of the 8th annual international conference on Mobile computing and networking
A game-theoretic study of CSMA/CA under a backoff attack
IEEE/ACM Transactions on Networking (TON)
IEEE Transactions on Information Theory
Distributed opportunistic scheduling for ad-hoc communications under delay constraints
INFOCOM'10 Proceedings of the 29th conference on Information communications
Distributed opportunistic scheduling with two-level probing
IEEE/ACM Transactions on Networking (TON)
A Control-Theoretic Approach to Distributed Optimal Configuration of 802.11 WLANs
IEEE Transactions on Mobile Computing
Distributed opportunistic scheduling for ad hoc communications with imperfect channel information
IEEE Transactions on Wireless Communications - Part 2
Opportunistic beamforming using dumb antennas
IEEE Transactions on Information Theory
Providing quality of service over a shared wireless link
IEEE Communications Magazine
Rate-Based Equilibria in Collision Channels with Fading
IEEE Journal on Selected Areas in Communications
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Distributed opportunistic scheduling (DOS) is inherently more difficult than conventional opportunistic scheduling due to the absence of a central entity that knows the channel state of all stations. With DOS, stations use random access to contend for the channel and, upon winning a contention, they measure the channel conditions. After measuring the channel conditions, a station only transmits if the channel quality is good; otherwise, it gives up the transmission opportunity. The distributed nature of DOS makes it vulnerable to selfish users: By deviating from the protocol and using more transmission opportunities, a selfish user can gain a greater share of wireless resources at the expense of "well-behaved" users. In this paper, we address the problem of selfishness in DOS from a game-theoretic standpoint. We propose an algorithm that satisfies the following properties: 1) When all stations implement the algorithm, the wireless network is driven to the optimal point of operation; and 2) one or more selfish stations cannot obtain any gain by deviating from the algorithm. The key idea of the algorithm is to react to a selfish station by using a more aggressive configuration that (indirectly) punishes this station. We build on multivariable control theory to design a mechanism for punishment that is sufficiently severe to prevent selfish behavior, yet not so severe as to render the system unstable. We conduct a game-theoretic analysis based on repeated games to show the algorithm's effectiveness against selfish stations. These results are confirmed by extensive simulations.