A multi-class probabilistic priority scheduling discipline for differentiated services networks

Differentiated Services (DiffServ) is a promising architecture for the next generation Internet due to its highly flexible, scalable and interoperable design. In DiffServ, scheduling disciplines play an important role in achieving service differentiation. In this paper, we extend the average delay analysis of the Probabilistic Priority (PP) scheduling discipline first proposed in [8] to the multi-class case. The PP discipline is based on the Strict Priority (SP) discipline with the difference that each priority queue is assigned a parameter pi ∈ [0, 1] which determines the probability that the queue is served when the queue is polled by the server. We derive the relationship between the average queueing delay for each class and these parameters, as well as the upper and lower bounds of the average queueing delay for each class. This relationship shows that PP can provide different Quality of Service (QoS) to different priority classes in a controllable way and is also able to provide relative and proportional differentiated services [14,15]. Simulation results of multi-class PP are presented here. In addition, we implemented multi-class PP on a DiffServ testbed and experimental results from this will also be discussed.