A robust packet scheduling algorithm for proportional delay differentiation services

The proportional delay differentiation (PDD) model is an important approach for relative differentiated services provisioning on the Internet. It aims to maintain pre-specified packet queueing-delay ratios between different classes of traffic at each hop. Existing PDD packet scheduling algorithms are able to achieve the goal in long time-scales when the system is highly utilized. The paper presents a new PDD scheduling algorithm, called Little's average delay (LAD), based on a proof of Little's law. It monitors the arrival rate and the cumulative delays of the packets from each traffic class, and schedules the packets according to their transient queueing properties so as to achieve the desired class delay ratios in both short and long time-scales. Simulation results show that, in comparison with other PDD scheduling algorithms, LAD can provide no worse level of service quality in long time-scales and more accurate and robust control over the delay ratio in short time-scales. In particular, LAD outperforms its main competitors significantly when the desired delay ratio is large.