即時性視訊訊務預測與頻寬協商機制於具服務品質保證之網路

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姓名

楊儒堯(Ru-Yao Yang) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

即時性視訊訊務預測與頻寬協商機制於具服務品質保證之網路
(Real-time video traffic prediction and bandwidth negotiation mechanism for QoS aware networks)

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摘要(中)

隨著網路上多媒體應用日益風行，即時性視訊的應用也逐漸成為矚目的焦點，然而視訊訊務對延遲以及封包遺失皆非常敏感，而且其資料流具有變動位元率的特性，又具有高變動的資料叢集現象，更因其為即時性的應用，無法事先得知訊務的分布特性，造成欲在網路上傳送即時視訊且要有良好的品質是件深具挑戰性的事。許多文獻提出各種即時性視訊訊務的預測技術，但很少討論到利用僅以預測的結果及該頻寬協商的機制，如何保證其畫面延遲並且符合使用者緩衝區容量大小的接受範圍之內。
在本篇論文中，我們針對即時性視訊服務提出一種新的即時性視訊訊務預測技術以及頻寬協商機制。即時性視訊訊務預測技術是依據畫面複雜度及偵測場景變換為基礎來做視訊訊務的預測，而頻寬協商機制則加入使用者緩衝區的使用限制，整合所提之視訊訊務預測技術並提出一套頻寬協商演算法則，使預測結果能同時滿足畫面延遲的限制以及使用者緩衝區的容量限制。實驗結果顯示，我們所提出的視訊訊務預測機制在畫面群位元率預測下，比傳統利用調適性最小錯誤均方線性預測器，可以減少10％至40％的預測錯誤量，更能利用簡單的參數設定，來調整重新協商次數與頻寬利用率的關係；而在使用者緩衝區的使用限制下，所提出的頻寬協商演算法確可在良好的頻寬利用率與合理的重新協商次數之下，滿足視訊訊務的延遲要求。

摘要(英)

Variable bit-rate (VBR) compressed video traffic is difficult to manage because it has strict delay and loss requirements. In particular, we cannot attain the bandwidth requirements for future frames in real-time video applications. Therefore, it is necessary to use a traffic prediction algorithm to estimate how much bandwidth should be reserved. Up to now, many literatures have proposed many video traffic prediction methods for bandwidth reservation. However, client buffer constraint and delay requirements are not considered in these methods.
In this thesis, we propose a new video traffic prediction scheme and a bandwidth negotiation scheme for real-time video applications. The video traffic prediction scheme is based on picture complexity analysis. The bandwidth negotiation scheme is based on the client buffer size constraint and the predictions from the proposed video traffic prediction scheme. It must decide when to renegotiate its service rate and what the new service rate should be. The performance of the strategy is studied using renegotiated constant bit-rate (RCBR) network service model. Simulation results show that using the proposed prediction scheme for predicting GOP rates reduces the prediction errors from 10% to 40% as compared to the conventional methods. The proposed bandwidth negotiation scheme also achieves high bandwidth utilization with reasonable negotiation times.

關鍵字(中)

★ 即時視訊訊務預測
★ 頻寬協商機制

關鍵字(英)

★ bandwidth neotiation mechanism
★ real- time video traffic prediction

論文目次

第一章序論 1
1.1研究動機與目的 1
1.2相關研究 2
1.3論文架構 4
第二章網際網路上的即時視訊服務 6
2.1 MPEG-4視訊壓縮技術 7
2.1.1 MPEG視訊編碼原理 8
2.1.2 MPEG-4加強以及新增功能 17
2.2即時性視訊訊務預測技術 22
2.2.1調適性最小錯誤均方線性預測器 22
2.2.2指數型RD預測器 24
2.2.3場景變換偵測之調適性最小錯誤均方線性預測器 25
2.3可提供服務品質的網路技術 26
2.4重新協商固定位元率 28
第三章即時性視訊訊務預測與輸出參數簡化 29
3.1畫面複雜度與編碼位元率之關係 31
3.2畫面場景變換的偵測 34
3.3畫面與畫面群之位元率預測 35
3.4降低重新協商次數之機制 38
第四章保證即時性視訊延遲之頻寬協商機制 44
4.1使用者緩衝區對於預測與頻寬協商機制的影響 44
4.1.1重新協商頻寬的時機 46
4.1.2最不容易溢滿或漏空的傳送頻寬 48
4.1.3固定緩和長度 51
4.2伺服器緩衝區對於頻寬利用率的影響 54
4.2.1因應伺服器緩衝區漏空的重新協商時機 55
4.2.2考慮伺服器緩衝區的新傳送頻寬 56
4.2.3同時考慮使用者及伺服器緩衝區的新傳送頻寬 58
第五章實驗結果與討論 61
5.1模擬環境說明 61
5.2模擬用之視訊序列及其參數之設定 62
5.3即時性視訊訊務預測的參數設定 64
5.4即時性視訊訊務預測的比較 66
5.4.1場景變換的偵測參數對位元率預測的影響 66
5.4.2位元率預測錯誤率之比較 67
5.4.3以畫面群預測為基礎的頻寬保留 70
5.4.4降低重新協商次數之比較 72
5.5緩衝區限制下頻寬協商機制的比較 75
5.5.1考慮使用者緩衝區的限制下 75
5.5.2使用者及伺服器緩衝區限制下之比較 78
第六章結論與未來工作 87
參考文獻 88
附錄A 91

參考文獻

[1]ISO/IEC JTC1/SC29/WG11, “MPEG-4 Video Verification Model version 18.0,” N3908, Jan. 2001.
[2]ISO/IEC JTC1/SC29/WG11, “Text of ISO/IEC 14496-2: 2001/COR2,” N5158, Oct. 2002.
[3]ISO/IEC JTC1/SC29/WG11, “MPEG-4 Visual: List of Problems Reported,” N5161, Oct. 2002.
[4]D. E. Wrege, E. W. Knightly, H. Zhang, and J. Liebeherr, “Deterministic Delay Bounds for VBR Video in Packet-Switching Networks: Fundamental Limits and Practical Trade-Offs,” IEEE/ACM Transactions on Networking, vol. 4, no. 3, pp. 352-362, Jun. 1996.
[5]E. W. Knightly and H. Zhang, “D-BIND: An Accurate Traffic Model for Providing QoS Guarantees to VBR Traffic,” IEEE/ACM Transactions on Networking, vol. 5, no. 2, pp. 219-231, Apr. 1997.
[6]M. Grossglauser, S. Keshav, and D. Tse, “RCBR：A Simple and Efficient Service for Multiple Time-scale Traffic,” IEEE/ACM Transactions on Networking, vol. 5, no. 6, pp. 741-755, Dec. 1997.
[7]A. M. Adas, “Using Adaptive Linear Prediction to Support Real-Time VBR Video Under RCBR Network Service Model,” IEEE/ACM Transactions on Networking, vol. 6, no. 5, pp. 635-644, Oct. 1998.
[8]M. J. Lee and J. K. Kim, “Video Traffic Prediction Using Source Information for Renegotiated CBR,” IEE Electronics Letters, vol. 36, no. 25, pp. 2072-2073, 7th Dec. 2000.
[9]S. J. Yoo, “Efficient Traffic Prediction Scheme for Real-Time VBR MPEG Video Transmission Over High-Speed Networks,” IEEE Transactions on Broadcasting, vol. 48, no. 1, pp. 10-18, Mar. 2002.
[10]J. D. Salehi, Z. L. Zhang, J. Kurose, D. Towsley “Supporting Stored Video: Reducing Rate Variability and End-to-end Resource Requirements Through Optimal Smoothing,” IEEE/ACM Transactions on Networking, vol. 6, no. 4, pp. 397-410, Aug. 1998.
[11]S. Sen, J. L. Rexford, J. K. Dey, J. F. Kurose and D. F. Towsley, “Online Smoothing of Variable-Bit-Rate Streaming Video,” IEEE Transactions on Multimedia, vol. 2, no. 1, pp. 37-48, Mar. 2000.
[12]J. Rexford, S. Sen, J. Dey, W. Feng, J. Kurose, J. Stankovic, and D. Towsely, “Online smoothing of live, variable-bit-rate video,” in Proc. Workshop on Network and Operating System Support for Digital Audio and Video, pp. 235-243 May 1997.
[13]Z. He, S. K. Mitra, “Optimum Bit Allocation and Accurate Rate Control for Video Coding via ρ-Domain Source Modeling,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 12, no. 10, pp. 840-849, Oct. 2002.
[14]A. M. Dawood, M. Ghanbari, “Content-Based MPEG Video Traffic Modeling,” IEEE Transactions on Multimedia, vol. 1, no. 1, pp. 77-87, Mar. 1999.
[15]W. A. C. Fernando, C. N. Canagarajah, and D. R. Bull, “Scene Change Detection algorithms for content-based video indexing and retrieval,” Electronics & Communication Engineering Journal, vol. 13, pp. 117-126, Jun. 2001.
[16]U. Gargi, R. Kasturi, and S. H. Strayer, “Performance characterization of video-shot-change detection methods,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 10, pp. 1-13, Feb. 2000.
[17]J. L. Mitchell, W. B. Pennebaker, C. E. Fogg, and D. J. LeGall, MPEG Video Compression Standard, Chapman & Hall, 1997.
[18]R. Talluri, “Error-Resilient Video Coding in the ISO MPEG-4 Standard,” IEEE Communications Magazine, vol. 36, no. 6, pp. 112-119, Jul. 1998.
[19]R. Braden, L.Zhang, Berson, S. Herzog, and S. Jamin, “Resource ReSerVation Protocol (RSVP),” RFC 2205, Sep. 1997.
[20]S.Shenker, C.Partidge, and R. Guerin, “Specification of Guaranteed Quality of Service,” RFC 2212, Sep. 1997.
[21]M. Wu, R. A. Joyce, H. S. Wong, L. Guan, S. Y. Kung, “Dynamic Resource Allocation via Video Content and Short-Term Traffic Statistics,” IEEE Transactions on Multimedia, vol. 3, no. 2, pp. 186-199, Jun. 2001.
[22]國立交通大學資訊科學所, “Internet內容遞送的演進,” 網路通訊, 中華民國九十一年二月.
[23]黃能富著, “區域網路與高速網路,” 維科出版社, 中華民國八十七年六月.
[24]S. Haykin, “Adaptive Filter Theory Fourth Edition,” Prentice-Hall, pp. 320-340, 2002.
[25]D. McDysan, “QoS & Traffic Management in IP & ATM Networks,” McGraw-Hill, pp. 43-55, 2000.

指導教授

張寶基(Pao-Chi Chang)

審核日期

2003-7-10

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