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Issue No.03 - March (2010 vol.9)

pp: 305-316

Yang Song , Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL, USA

Chi Zhang , Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL, USA

Yuguang Fang , Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL, USA

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TMC.2009.111

ABSTRACT

In this work, the stochastic traffic engineering problem in multihop cognitive wireless mesh networks is addressed. The challenges induced by the random behaviors of the primary users are investigated in a stochastic network utility maximization framework. For the convex stochastic traffic engineering problem, we propose a fully distributed algorithmic solution which provably converges to the global optimum with probability one. We next extend our framework to the cognitive wireless mesh networks with nonconvex utility functions, where a decentralized algorithmic solution, based on learning automata techniques, is proposed. We show that the decentralized solution converges to the global optimum solution asymptotically.

INDEX TERMS

wireless mesh networks, cognitive radio, learning automata, telecommunication traffic,learning automata techniques, traffic engineering, multihop cognitive wireless mesh networks, network utility maximization,Stochastic processes, Telecommunication traffic, Spread spectrum communication, Wireless mesh networks, Interference, Cognitive radio, Utility programs, Relays, Throughput, Frequency,learning algorithms., Cognitive networks, network utility maximization

CITATION

Yang Song, Chi Zhang, Yuguang Fang, "Stochastic Traffic Engineering in Multihop Cognitive Wireless Mesh Networks",

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