The weighted majority algorithm
Information and Computation
Scaling of multicast trees: comments on the Chuang-Sirbu scaling law
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
A new model for packet scheduling in multihop wireless networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Multiple Access in Ad-Hoc Wireless LANs with Noncooperative Stations
NETWORKING '02 Proceedings of the Second International IFIP-TC6 Networking Conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; and Mobile and Wireless Communications
Gambling in a rigged casino: The adversarial multi-armed bandit problem
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Impact of interference on multi-hop wireless network performance
Proceedings of the 9th annual international conference on Mobile computing and networking
Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing
Proceedings of the 11th annual international conference on Mobile computing and networking
Weighted coloring based channel assignment for WLANs
ACM SIGMOBILE Mobile Computing and Communications Review
Prediction, Learning, and Games
Prediction, Learning, and Games
Sufficient rate constraints for QoS flows in ad-hoc networks
Ad Hoc Networks
A game approach for multi-channel allocation in multi-hop wireless networks
Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
Performance analysis of the IEEE 802.11 distributed coordination function
IEEE Journal on Selected Areas in Communications
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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.