Xiaolong Jin and Geyong Min -- Abstract

Performance Modelling of A Hybrid Scheduling Scheme under Self-Similar Network Traffic

Traffic self-similarity (i.e., noticeable burstiness over multiple time scales) has been discovered to be a ubiquitous phenomenon in modern communication networks and multimedia systems. Self-similar traffic can considerably deteriorate user-perceived Quality- of-Service (QoS) and has drawn significant interest and received tremendous research efforts from both academia and industry. Due to its fractal-like nature, performance modelling of self-similar traffic poses greater challenges and exhibits more complexity than that of traditional non-bursty traffic.

The hybrid scheduling scheme that integrates the well-known Priority Queueing (PQ) and Generalized Processor Sharing (GPS) has been suggested as a promising mechanism for the provisioning and implementation of differentiated QoS. In this talk, we will present a new analytical model we have recently developed for the hybrid PQ-GPS scheduling scheme subject to self-similar traffic.

In order to make the challenging performance modelling problem tractable, we propose a novel flow-decomposition approach that can equivalently divide the PQ-GPS system into a group of Single-Server Single-Queue (SSSQ) systems and derive their service capacities. Based on the Large Deviation Principle and by virtue of the equivalent relationship between these SSSQ systems and the original PQ-GPS system, we derive the queue length distributions and loss probabilities of individual traffic flows in the hybrid system. The validity of the proposed flow-decomposition approach and the accuracy of the analytical model are demonstrated by comparing analytical results to those obtained through extensive simulation experiments of theactual system.

Page modified May 2007 by Richard G. Clegg