Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Optimal flow control and routing in multi-path networks
Performance Evaluation - Special issue: Internet performance and control of network systems
Proceedings of the 11th annual international conference on Mobile computing and networking
Characterizing the capacity region in multi-radio multi-channel wireless mesh networks
Proceedings of the 11th annual international conference on Mobile computing and networking
Multichannel mesh networks: challenges and protocols
IEEE Wireless Communications
IEEE Transactions on Wireless Communications
A tutorial on cross-layer optimization in wireless networks
IEEE Journal on Selected Areas in Communications
On optimal distributed channel allocation for access points in WLANs
NETWORKING'11 Proceedings of the IFIP TC 6th international conference on Networking
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This paper studies how to design distributed resource allocation in multi-radio multi-channel wireless mesh networks with the objective of maximizing the network utility. We address the problem via a cross-layer approach with a joint consideration of multi-path routing, congestion control, scheduling, radio allocation and channel assignment. The problem is formulated as a mixed-integer non-linear programming (MINLP), which normally requires a centralized solution and hence has prohibitively high computation complexity. We propose a two-phase distributed mechanism to substantially reduce the computation load and communications overhead. Firstly, we relax the integral variables and obtain a convex programming, which serves as the upper bound of the optimal utility. Secondly, we propose a distributed scheme to approach the upper bound within the feasible region of the optimization problem. To evaluate the performance of the distributed algorithm, we compare it to the exact optimal solution to the MINLP objective function, which is obtained by using a centralized branch-and-bound method. Simulation results show that the performance of our proposed distributed algorithm is close to the optimal solution.