Abstract

The efficient transportation of real-time Variable Bit Rate (VBR) video traffic in the high-speed networks has been an area of active research. An important issue is the simplicity with which the bandwidth allocation and scheduling schemes can be executed online with real-time constraints in the future high-speed networks. The correlation properties of the VBR video traffic make the predictor-based online traffic adaptation techniques attractive. We developed a novel predictor-based dynamic bandwidth allocation (PDBA) scheme for short-term resource management and studied its queuing performance. In order to reduce the effects of the prediction errors on the queuing system and hence the underutilization of reserved bandwidth, a novel short-term controller (STC) that works at the cell-level has been introduced and the system has been called the PDBA–STC system. This online VBR video traffic prediction-based traffic management scheme has low complexity and is suitable for implementation in high-speed networks Ranganathan et al. [N. Ranganathan, R. Anand, G. Chiruvolu, A VLSI ATM architecture for VBR traffic, Proc. IEEE International Conference on VLSI Design, 1998, pp. 420–427] and has been demonstrated to provide better performance than other existing simple schemes. This paper also investigates the predictability of VBR video traffic that exhibits long-range dependence (LRD) based on a fractional ARIMA (1,d,0) model. The short-range dependent (SRD) Auto Regressive (AR) model for prediction of VBR video traffic has also been considered for evaluation of the proposed dynamic bandwidth allocation scheme and the performance has been compared to that of LRD-based prediction. Finally, a summary and future research have been discussed.

Author Keywords: Traffic management; VBR-video; Long-range dependence models; Short-range dependence models

Article Outline

1. Introduction

2. Characteristics of video traffic and their implications

2.1. The LRD characteristics of VBR video traffic

2.1.1. Prediction errors

3. Proposed architecture and algorithms

3.1. Overview of the predictor-based server architecture

3.2. PDBA–STC algorithm

3.3. Computational requirements

4. Performance evaluation

5. Fairness of bandwidth allocation by the PDBA–STC scheme

6. Conclusions and future research

Acknowledgements

References