Fair allocation of bandwidth and maximization of channel utilization are two important issues when designing a contention-based wireless medium access control (MAC) protocol. However, fulfilling both design goals at the same time is very difficult. Considering the problem in the IEEE 802.11 wireless local area networks (WLANs), in this work we propose a method using a p-persistent enhanced DCF, called P-IEEE 802.11 DCF, to achieve weighted fairness and efficient channel utilization among multiple priority classes in a WLAN. Its key idea is that when the back-off timer of a node reaches zero, the transmission probability is properly controlled to reflect the relative weights among data traffic flows so as to maximize the aggregate throughput and to minimize the frame delay at the same time. In particular, we obtain the optimal transmission probability based on a theoretical analysis, and also provide an approximation to this probability. The derived optimal and approximation are all evaluated numerically and simulated with different scenarios. The results show that the proposed method can fulfill our design goals under different numbers of priority classes and different numbers of nodes.

This paper proposes dynamic distributed unicast and multicast routing algorithms for multiple classes of QoS guaranteed networks. Each link in such a network is assumed to be able to provide multiple classes of QoS guarantee by reserving various amounts of resource. A distributed unicast routing algorithm, DCSP (Distributed Constrained Shortest Path), for finding a QoS constrained least cost path between each O-D (Originating-Destination) pair, is proposed first. Two class reduction schemes, the linear and logarithmic policies, are develpoed to prevent exponential growth of the number of end-to-end QoS classes. Based on DCSP, two distributed multicast routing algorithms, DCSPT (Distributed Constrained Shortest Path Tree) and DTM (Distributed Takahashi and Mutsuyama), are proposed to find QoS constrained minimum cost trees. Numerical results indicate that DCSP strongly outperforms previously proposed centralized algorithms and it works better with the linear class reduction method. For the multicast routing algorithms, the DCSPT with linear class reduction method yields the best performance of all multicast routing algorithms.