1687-6180-2007-087136 1687-6180 Research Article <p>Dynamic Bandwidth Allocation Based on Online Traffic Prediction for Real-Time MPEG-4 Video Streams</p> LiangYaoyaliang@vt.edu HanMeimhn@vt.edu

Department of Electrical and Computer Engineering, Advanced Research Institute, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA

 EURASIP Journal on Advances in Signal Processing 1687-6180 2007 2007 1 087136 http://asp.eurasipjournals.com/content/2007/1/087136 10.1155/2007/87136 128200515420064620061392006 2007Liang and Han

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 real-world 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.

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