Delay analysis of a probabilistic priority discipline

Abstract

In computer networks, the Strict Priority (SP) discipline is perhaps the most common and simplest method to schedule packets from different classes of applications, each with diverse performance requirements. With this discipline, however, packets at higher priority levels can starve packets at lower priority levels. To resolve this starvation problem, we propose to assign a parameter to each priority queue in the SP discipline. The assigned parameter determines the probability or extent by which its corresponding queue is served when the queue is polled by the server. We thus form a new packet service discipline, referred to as the Probabilistic Priority (PP) discipline. By properly adjusting the assigned parameters, not only is the performance of higher priority classes satisfied, but also the performance of lower priority classes can be improved. This paper analyzes the delay performance of the PP discipline. A decomposition approach is proposed for calculating the average waiting times and their bounds are studied. Two approximation approaches are proposed to estimate the waiting times. Simulation results that validate the numerical analysis are presented and examined. A numerical example which demonstrates the use of the PP discipline to achieve service differentiation is presented. This example also shows how the assigned parameters can be determined from the results of analysis mentioned above.