Dynamic Bandwidth Allocation Based on Online Traffic Prediction for Real-Time MPEG-4 Video Streams
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Research Article Dynamic Bandwidth Allocation Based on Online Traffic Prediction for Real-Time MPEG-4 Video Streams Yao Liang and Mei Han Department of Electrical and Computer Engineering, Advanced Research Institute, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA Received 12 August 2005; Revised 15 April 2006; Accepted 4 June 2006 Recommended by Ming-Ting Sun The distinct characteristics of variable bit rate (VBR) video traffic and its quality of service (QoS) constraints have posed a unique challenge on network resource allocation and management for future integrated networks. Dynamic bandwidth allocation attempts to adaptively allocate resources to capture the burstiness of VBR video traffic, and therefore could potentially increase network utilization substantially while still satisfying the desired QoS requirements. We focus on prediction-based dynamic bandwidth allocation. In this context, the multiresolution learning neural-network-based traffic predictor is rigorously examined. A well-known-heuristic based approach RED-VBR scheme is used as a baseline for performance evaluation. Simulations using realworld MPEG-4 VBR video traces are conducted, and a comprehensive performance metrics is presented. In addition, a new concept of renegotiation control is introduced and a novel renegotiation control algorithm based on binary exponential backoff (BEB) is proposed to efficiently reduce renegotiation frequency. Copyright © 2007 Hindawi Publishing Corporation. All rights reserved.
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INTRODUCTION
Variable bit rate (VBR) video traffic, generated from diverse multimedia applications, is expected to be a significant portion of traffic in future integrated services networks. VBR videos require a sophisticated network resource allocation and management (NRAM) mechanism to support their strict delay and loss requirements. Due to the nature that VBR videos typically exhibit burstiness over multiple time scales [3, 4], it poses a unique challenge to the design of NRAM mechanism to achieve high overall network utilization, while still preserving the desired quality of service (QoS) requirements. The challenge is essential particularly for real-time VBR video transmission in which the traffic trace is unknown in advance. Clearly, any static allocating bandwidth (i.e., allocating exactly once for the entire video transmission session) for real-time VBR video streams would result in either inefficient utilization of bandwidth due to over allocation of resource or insufficient to support the required QoS due to the under allocation of resource. Dynamic bandwidth allocation attempts to adaptively allocate resources to capture the burstiness of VBR video traffic, and hence could be particularly promising for real-time VBR video transmissions [2, 5, 6]. One fundamental issue
in any dynamic bandwidth allocation mechanism is how to sense the traffic dynamics in advance in order to determine the resource needs. One approach is to devise some heuristic method to estimate the future traffic characteristics, such as RED-VBR
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