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.
Highlights
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
A long-term VBR video traffic predictor is certainly desirable in such a study, because singleframe-ahead network traffic predictors (e.g., [5, 9, 10, 12]) would result in too frequent bandwidth renegotiations and the heavy reallocation control overhead which might eventually eliminate all merits that could be obtained from online traffic prediction
The key contributions of our work are (1) noting that a realistic service policy in trace-driven simulation for dynamic resource allocation study is critical in revealing and understanding fundamental aspects of predictive dynamic bandwidth allocation approach; (2) showing significant improvement in performance of our predictive dynamic bandwidth allocation approach based on long-term online traffic prediction over RED-VBR and the predictive dynamic bandwidth allocation based on single-step-ahead traffic prediction; and (3) introducing the new concept of renegotiation control, and proposing and examining a binary exponential backoff (BEB)-based renegotiation control method
Summary
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. A long-term VBR video traffic predictor is certainly desirable in such a study, because singleframe-ahead network traffic predictors (e.g., [5, 9, 10, 12]) would result in too frequent bandwidth renegotiations and the heavy reallocation control overhead which might eventually eliminate all merits that could be obtained from online traffic prediction. To this end, MRL-NN traffic predictor developed in [1] is employed and examined.
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