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自相似模型仿真ATM网络VBR视频源研究 被引量：1

Study of Modeling ATM VBR Video Traffic Using Self-similar Process
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摘要 仿真过程采用了一种新的异步传输模式 (ATM)视频源建模方法 ,即长期相关性分析和自相似模型方法 ,使用了自相似模型中的分形高斯噪声 (FGN)模型 .FGN过程的产生采用了Hosking算法和反变换法 .在仿真具体实现过程中改进了现有FGN模型仿真算法的不足 ,从而使产生的过程既充分考虑到实际可变比特率 (VBR)视频源序列的长期相关性 ,又兼顾了序列的短期相关性 ,同时给出了仿真结果与实际源统计特性的比较和验证 .比较结果表明 。 ATM is the basic transmission and switching technology used in the further B ISDN network.This paper proposes an efficient method for video traffic modeling,called long range dependence analysis and self similar traffic modeling.Using FGN process,one of self similar processes and making improvements on the FGN algorithm to model both SLD and LRD of the empirical sequence autocorrelation structure,we present simulation results of synthetic data and compare with results based on empirical video sequence.Basing on statistical analysis and graphical tests of the data got from the empirical video sequence,we come to the conclusion that self similar process is ideal for modeling VBR video traffic.
作者 刘力纬 陈峥 阮永良
机构地区 朗讯科技光网络中国有限公司 同济大学沪西校区计算机科学与工程系
出处 《同济大学学报（自然科学版）》 EI CAS CSCD 北大核心 2001年第4期440-443,共4页 Journal of Tongji University:Natural Science
关键词 异步传输模式 视频源建模 自相似过程 分形高斯噪声 自相似模型仿真 ATM网络 可变比特率视频源 asynchronous transfer mode video traffic modeling self similar process long range dependent fractal gaussian noise
分类号 TN919.85 [电子电信—通信与信息系统] TP393.01 [自动化与计算机技术—计算机应用技术]
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参考文献5

  • 1[1]Garrett M W, Willinger W. Analysis, modeling and generation of self-similar VBR video traffic [A]. Proc ACM Sigcornm 94 [C]. [s.l.]:ACM, 1994. 269-280.
  • 2[2]Hosking J R M. Modeling persistence in hydrological time series using fractional differencing[J]. Water Resources Research, 1984,20 (12):1898-1908.
  • 3[3]Ramsey F L. Characterization of the partial autocorrelation function[J]. The Annals of Statistics, 1974,2(6):1296- 1301.
  • 4[4]Stefano G, Pagano M. A new call admission control scheme based on the self similar nature of multimedia traffic[A]. Proceedings IEEE ICC'96[C]. [s.l.]: IEEE ICC, 1996. 1612-1618.
  • 5[5]Heyman D P, Lakshrnan T V. What are the implications of long-range dependence of VBR video traffic engineering[J]. IEEE/ACM Trans On Net, 1996,4(3) :301-317.

同被引文献22

  • 1AbdeInaser Adas. Traffic Models in Broadband Networks[J]. IEEE Communications Magazine, 1997,35(7):82-89.
  • 2Liu H, Ansari N, Shi Y Q. The Tail of A Simple Accurate MPEG Video Traffic Model[A]. In:Communications, 2001. ICC 2001. IEEE International Conference on[C]. 2001, 4. 1042-1046.
  • 3Derong Liu, Ender I Sára. A New Traffic Model for MPEG Encoded Video in ATM Networks[A]. In:Computer Communications and Networks, 2000. Proceedings. Ninth International Conference on[C]. 2000. 258-263.
  • 4Nikolaos D Doulamis, Anastasios D Doulamis, George E Konstantoulakis, George I Stassinpoulos. Efficient Modeling of VBR MPEG-1 Coded Video Sources[J]. IEEE Trans. on Circuits and Systems for Video Technology, 2000, 10(1) : 93-112.
  • 5Skelly P, Schwartz M, Dixit S. A Histogram-Based Model for Video Traffic Behavior in an ATM Multiplexer[J]. IEEE/ACM Trans. On Networking, 1993, 1(4) : 446-459.
  • 6Melamed B, Pendarakis D E. Modeling Full-Length VBR Video Using Markov-Renewal-Modulated TES Models[J]. IEEE/ACM Trans. On Networking, 1997, 5(1) : 600-611.
  • 7Garrett M W, Willinger W. Analysis, Modeling and Generation of Self-Similar VBR Video Traffic[A]. In:Proc. ACM SIGCOMM'94[C]. London, U. K.: 1994. 269-280.
  • 8Krunz M M, Makowski A M. Modeling Video Traffic Using M/G/ Input Process: A Compromise between Markovian and LRD Models[J]. IEEE Journal on Selected Areas in Comm., 1998, 16(5) : 733-748.
  • 9Heyman D P, Lakeshman T V. Source Models for VBR Broadcast-Video Traffic[J]. IEEE/ACM Trans. On Networking, 1996, 4(1) : 40-48.
  • 10Derong Liu, Ender I Sára, Wei Sun. Nested Auto-regressive Progress for MPEG-Encoded Video Traffic Modeling[J]. IEEE Trans. On Circuits and Systems for Video Technology, 2001, 11(2) : 169-183.

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同济大学学报（自然科学版）
2001年 第4期

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