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SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
The Nonstochastic Multiarmed Bandit Problem
SIAM Journal on Computing
On the capacity improvement of ad hoc wireless networks using directional antennas
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The complexity of computing a Nash equilibrium
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Regret minimization and the price of total anarchy
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Approximation schemes for wireless networks
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Fast deterministic distributed maximal independent set computation on growth-bounded graphs
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The capacity of wireless networks
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Structure and algorithms in the SINR wireless model
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Efficiency of Wireless Networks: Approximation Algorithms for the Physical Interference Model
Foundations and Trends® in Networking
Link scheduling in wireless networks with successive interference cancellation
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Nearly optimal bounds for distributed wireless scheduling in the SINR model
ICALP'11 Proceedings of the 38th international conference on Automata, languages and programming - Volume Part II
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In this paper we consider the problem of maximizing wireless network capacity (a.k.a. one-shot scheduling) in both the protocol and physical models. We give the first distributed algorithms with provable guarantees in the physical model, and show how they can be generalized to more complicated metrics and settings in which the physical assumptions are slightly violated. We also give the first algorithms in the protocol model that do not assume transmitters can coordinate with their neighbors in the interference graph, so every transmitter chooses whether to broadcast based purely on local events. Our techniques draw heavily from algorithmic game theory and machine learning theory, even though our goal is a distributed algorithm. Indeed, our main results allow every transmitter to run any algorithm it wants, so long as its algorithm has a learning-theoretic property known as no-regret in a game-theoretic setting.