End-to-End Statistical Delay Service under GPS and EDF Scheduling: A Comparison Study

Generalized Processor Sharing (GPS) has gained much popularity in recent years as a simple and effective scheduling mechanism for the provisioning of Quality of Service (QoS) in emerging high-speed networks. For supporting deterministic end-to-end delay guarantees, GPS is known to be sub-optimal in comparison to the Earliest Deadline First (EDF) scheduling discipline; nevertheless it is often prefered over EDF due to its simplicity. In this paper, using analytical frameworks developed recently in the literature, we reassess the merits of GPS as compared to EDF in the setting of statistical delay service. Our contributions are threefold. The statistical frameworks in the literature enable the aggregate losses (i.e., delay bound violations) at an EDF scheduler to be estimated – our first contribution, therefore, is to develop a mechanism that allows the aggregate losses to translate to per-flow guarantees. This is achieved by means of a simple packet discard scheme that drops packets fairly when delay violations are imminent at the EDF scheduler. The discard mechanism has a constant complexity and is feasible for implementation in current packet switches. The ability to derive the per-flow guarantees from the agregate allows a direct comparison between EDF and GPS – our next contribution, therefore, is to show for various traffic mixes with given per-flow loss constraints that EDF offers consistently larger schedulable regions than GPS, both in the single-hop and multi-hop setting. As our final contribution, we argue that the use of GPS for statistical delay support is inherently problematic. We demonstrate that achieving the maximal schedulable regions under GPS could necessitate dynamic resynchronization of the GPS weights, an operation considered infeasible for practical implementation.