Issue No. 03 - March (2010 vol. 9)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TMC.2009.111
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
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.
wireless mesh networks, cognitive radio, learning automata, telecommunication traffic
Yang Song, Chi Zhang and Yuguang Fang, "Stochastic Traffic Engineering in Multihop Cognitive Wireless Mesh Networks," in IEEE Transactions on Mobile Computing, vol. 9, no. 3, pp. 305-316, 2010.