Sojourn Time Approximations for a Discriminatory Processor Sharing Queue

We study a multiclass time-sharing discipline with relative priorities known as discriminatory processor sharing (DPS), which provides a natural framework to model service differentiation in systems. The analysis of DPS is extremely challenging, and analytical results are scarce. We develop closed-form approximations for the mean conditional (on the service requirement) and unconditional sojourn times. The main benefits of the approximations lie in its simplicity, the fact that it applies for general service requirements with finite second moments, and that it provides insights into the dependency of the performance on the system parameters. We show that the approximation for the mean conditional and unconditional sojourn time of a customer is decreasing as its relative priority increases. We also show that the approximation is exact in various scenarios, and that it is uniformly bounded in the second moments of the service requirements. Finally, we numerically illustrate that the approximation for exponential, hyperexponential, and Pareto service requirements is accurate across a broad range of parameters.