Optimal rate allocation in wireless networks with delay constraints

The optimal rate allocation problem with end-to-end delay constraints in wireless networks is highly challenging due to the dynamics incurred by delay related factors, such as traffic arrival pattern, queuing process, and wireless resource sharing mechanism. In this paper, we solve the problem through a utility maximization framework with two sets of constraints: (1) capacity and schedulability constraints and (2) end-to-end delay constraints. The end-to-end delay of a flow can be adjusted by controlling the per-link delays via a novel parameter called Virtual Link Capacity Margin (VLCM), which is the measurement of the gap between the schedulable link capacity and the maximum allowable flow rate over a link. This optimization problem can be solved via its dual decomposition through two prices derived with regard to the constraints: the link congestion price that reflects the relationship between the traffic load and the capacity of a link, and the flow delay price that reflects the margin between the average packet delay and the delay constraint of a flow. We prove that the algorithm converges to the optimal solution under the M/M/1 queuing model. We have also discussed using our algorithm under generalized traffic patterns, where we use link delay functions to formulate the relationship between VLCM and the average link delay. The algorithm is implemented distributedly via joint wireless link scheduling, VLCM adjustment and congestion control. Extensive experiments are conducted over diverse network topologies and traffic arrival models. The experimental results show that our algorithm is able to achieve optimal rate allocation while satisfying the end-to-end delay constraints.