Distributed optimization of Contention Windows in 802.11e MAC to provide QoS differentiation and maximize channel utilization

We propose a distributed algorithm for optimizing the Contention Windows in IEEE 802.11e based WLANs with the dual intention of providing fine-grained QoS and maximizing the channel utilization. The underlying concept behind the algorithm is modeling the network state as a function of MAC parameters and solving this analytical model constrained by the QoS requirements of multiple nodes. The main contribution of this paper is the completely distributed realization of this concept. The problem appears as a system of non-linear equations which is solved by an iterative gradient-based method. Distributed solution is achieved by first decoupling the equations and second by implicit message passing through local measurements. This allows local computation of partial differentials and residuals of the iterative process. Local measurements serve as inputs for the next iterative step and as natural feedback mechanism to handle dynamic channel conditions. Convergence of iterations is ensured through progressive target setting of QoS requirements. Extensive simulation results and a proof of concept with a test bed show that the algorithm achieves fine-grained QoS differentiation while minimizing delays, collisions and packet losses. As a result, when the network scales, the algorithm is shown to maximize the channel utilization and maintain a near optimal total throughput of the system. Finally, sub-minute convergence time makes the algorithm suitable for real-time flows.