Dynamic Bandwidth Allocation Based on Online Traffic Prediction for Real-Time MPEG-4 Video Streams. (13th September 2006)

• Record Type: Journal Article
• Authors: Liang Liang, Yao Yao; Han Han, Mei Mei
• Other Names: Sun Sun Ming-Ting Ming-Ting Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2007(2007)
• Publication Date: 2006-09-13
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2007/87136
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : 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.