Dynamic bandwidth allocation based on online traffic prediction for real-time MPEG-4 video streams

被引：0

作者：

Liang Y. ^{[1
]}

Han M. ^{[1
]}

机构：

[1] Department of Electrical and Computer Engineering, Advanced Research Institute, Virginia Polytechnic Institute and State University, Arlington

来源：

Eurasip. J. Adv. Sign. Process. | 2007年 / 2007卷 / 1期

关键词：

Algorithms - Bandwidth - Computer simulation - Heuristic methods - Neural networks - Quality of service - Telecommunication traffic - Video signal processing;

D O I：

10.1155/2007/87136

中图分类号：

学科分类号：

摘要：

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.

引用

共 17 条

[1]

Garrett M.W., Willinger W., Analysis, modeling and generation of self-similar VBR video traffic, Proceedings of the ACM SIGCOMM Conference on Communications Architectures, Protocols and Applications, pp. 269-280, (1994)

[2]

Rathgeb E.P., Modeling and performance comparison of policing mechanisms for ATM networks, IEEE Journal on Selected Areas in Communications, 9, 3, pp. 325-334, (1991)

[3]

Zhang H., Knightly E.W., RED-VBR: A renegotiation-based approach to support delay-sensitive VBR video, Multimedia Systems, 5, 3, pp. 164-176, (1997)

[4]

Chong S., Li S., Ghosh J., Predictive dynamic bandwidth allocation for efficient transport of real-time VBR video over ATM, IEEE Journal on Selected Areas in Communications, 13, 1, pp. 12-23, (1995)

[5]

Wu M., Joyce R.A., Wong H.-S., Guan L., Kung S.-Y., Dynamic resource allocation via video content and short-term traffic statistics, IEEE Transactions on Multimedia, 3, 2, pp. 186-199, (2001)

[6]

Liang Y., Real-time VBR video traffic prediction for dynamic bandwidth allocation, IEEE Transactions on Systems, Man, and Cybernetics - Part C: Applications and Reviews, 34, 1, pp. 32-47, (2004)

[7]

Le Boudec J.-Y., Verscheure O., Optimal smoothing for guaranteed service, IEEE/ACM Transactions on Networking, 8, 6, pp. 689-696, (2000)

[8]

Rexford J., Sen S., Dey J., Online smoothing of live, variable-bit-rate video, Proceedings of the IEEE International Workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV '97), pp. 235-243, (1997)

[9]

Adas A.M., Using adaptive linear prediction to support real-time VBR video under RCBR network service model, IEEE/ACM Transactions on Networking, 6, 5, pp. 635-644, (1998)

[10]

Chiruvolu G., Sankar R., Ranganathan N., VBR video traffic management using a predictor-based architecture, Computer Communications, 23, 1, pp. 62-70, (2000)

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