tailieunhanh - Báo cáo hóa học: " Research Article Dynamic Bandwidth Allocation Based on Online Traffic Prediction for Real-Time MPEG-4 Video Streams"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Dynamic Bandwidth Allocation Based on Online Traffic Prediction for Real-Time MPEG-4 Video Streams | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 87136 10 pages doi 2007 87136 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 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. Copyright 2007 Hindawi Publishing Corporation. All rights reserved. 1. 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