A QoS-enhanced intelligent stochastic real-time packet scheduler for multimedia IP traffic

Abstract

A re-configurable, QoS-enhanced intelligent stochastic real-time optimal fair packet scheduler, QUEST, for IP routers is proposed and investigated. The objective is to maximize the system QoS subject to the constraint that the processor utilization is kept at 100%. All past work on router schedulers for multimedia traffic were of earlier generation, in that they focused on maximizing utilization whereas being QoS-aware but without explicitly maximizing the QoS. Keeping utilization fixed at nearly 100%, QoS is dynamically maximized, thus moving to the next generation. QUEST’s other unique advantages are three-fold. First, it solves the challenging problem of starvation for low priority processes; second, it solves the major bottleneck of Earliest Deadline First scheduler’s failure at heavy traffic loads. Finally, QUEST offers the benefit of arbitrarily pre-programming the process utilization ratio. Three classes of multimedia IP traffic, namely, VoIP, IPTV and HTTP have been considered. Two most important QoS metrics, namely, packet loss rate (PLR) and mean waiting time, are addressed. All claims are supported by discrete event and Monte Carlo simulations. The proposed scheduler outperforms benchmark schedulers and offers 37% improvement in packet loss rate and 23% improvement in mean waiting time over the best competing current scheduler Accuracy-aware EDF. The proposed scheduler was validated in a test-bed platform of a NetFPGA® router and results were observed with Paessler® PRTG network monitor.