Long-range dependence in variable-bit-rate video traffic

We analyze 20 large sets of actual variable-bit-rate (VBR) video data, generated by a variety of different codecs and representing a wide range of different scenes. Performing extensive statistical and graphical tests, our main conclusion is that long-range dependence is an inherent feature of VBR video traffic, i.e., a feature that is independent of scene (e.g., video phone, video conference, motion picture video) and codec. In particular, we show that the long-range dependence property allows us to clearly distinguish between our measured data and traffic generated by VBR source models currently used in the literature. These findings give rise to novel and challenging problems in traffic engineering for high-speed networks and open up new areas of research in queueing and performance analysis involving long-range dependent traffic models. A small number of analytic queueing results already exist, and we discuss their implications for network design and network control strategies in the presence of long-range dependent traffic. >

[1]  C. Granger Long memory relationships and the aggregation of dynamic models , 1980 .

[2]  T. V. Lakshman,et al.  Statistical analysis and simulation study of video teleconference traffic in ATM networks , 1992, IEEE Trans. Circuits Syst. Video Technol..

[3]  Ya-Qin Zhang,et al.  Motion-classified autoregressive modeling of variable bit rate video , 1993, IEEE Trans. Circuits Syst. Video Technol..

[4]  Walter Willinger,et al.  Self-Similarity in High-Speed Packet Traffic: Analysis and Modeling of Ethernet Traffic Measurements , 1995 .

[5]  Basil S. Maglaris,et al.  Models for packet switching of variable-bit-rate video sources , 1989, IEEE J. Sel. Areas Commun..

[6]  C. Heyde Smoothed periodogram asymptotics and estimation for processes and fields with possible long-range dependence , 1993 .

[7]  Amy R. Reibman,et al.  Analysis of a video multiplexer using TES as a modeling methodology , 1991, IEEE Global Telecommunications Conference GLOBECOM '91: Countdown to the New Millennium. Conference Record.

[8]  B. G. Haskell Buffer and channel sharing by several interframe picturephone® coders , 1972 .

[9]  M. Taqqu A Bibliographical Guide to Self-Similar Processes and Long-Range Dependence , 1986 .

[10]  B. Mandelbrot,et al.  Fractional Brownian Motions, Fractional Noises and Applications , 1968 .

[11]  Jean C. Walrand,et al.  Effective bandwidths for multiclass Markov fluids and other ATM sources , 1993, TNET.

[12]  M. Taqqu,et al.  Large-Sample Properties of Parameter Estimates for Strongly Dependent Stationary Gaussian Time Series , 1986 .

[13]  M. Taqqu Convergence of integrated processes of arbitrary Hermite rank , 1979 .

[14]  Ilkka Norros,et al.  A storage model with self-similar input , 1994, Queueing Syst. Theory Appl..

[15]  Hamid Ahmadi,et al.  Equivalent Capacity and Its Application to Bandwidth Allocation in High-Speed Networks , 1991, IEEE J. Sel. Areas Commun..

[16]  Jan Beran Estimation, testing and prediction for self-similar and related processes , 1986 .

[17]  H. Graf,et al.  Long-range correlations and estimation of the self-similarity parameter , 1983 .

[18]  H. Künsch Discrimination between monotonic trends and long-range dependence , 1986 .

[19]  Benoit B. Mandelbrot,et al.  Fractal Geometry of Nature , 1984 .

[20]  V. Klemeš The Hurst Phenomenon: A puzzle? , 1974 .

[21]  Yoshihiro Yajima,et al.  ON ESTIMATION OF LONG-MEMORY TIME SERIES MODELS , 1985 .

[22]  Nick Duffield,et al.  Large deviations and overflow probabilities for the general single-server queue, with applications , 1995 .

[23]  Sally Floyd,et al.  Wide area traffic: the failure of Poisson modeling , 1995, TNET.

[24]  E. H. Lloyd,et al.  The expected value of the adjusted rescaled Hurst range of independent normal summands , 1976 .

[25]  J. Geweke,et al.  THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS , 1983 .

[26]  Mark W. Garrett,et al.  Modeling and generation of self-similar vbr video traffic , 1994, SIGCOMM 1994.

[27]  W. Whitt,et al.  Asymptotics for steady-state tail probabilities in structured markov queueing models , 1994 .

[28]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.

[29]  Jan Beran,et al.  Statistics for long-memory processes , 1994 .

[30]  Henry J. Fowler,et al.  Local Area Network Traffic Characteristics, with Implications for Broadband Network Congestion Management , 1991, IEEE J. Sel. Areas Commun..

[31]  R. Bhattacharya,et al.  THE HURST EFFECT UNDER TRENDS , 1983 .

[32]  P. Skelly,et al.  A histogram-based model for video traffic behavior in an ATM multiplexer , 1993, TNET.

[33]  N. Ohta,et al.  Packet video transmission through ATM networks , 1989, IEEE Global Telecommunications Conference, 1989, and Exhibition. 'Communications Technology for the 1990s and Beyond.

[34]  John Cosmas,et al.  Characterization of Video Codecs as Autoregressive Moving Average Processes and Related Queueing System Performance , 1991, IEEE J. Sel. Areas Commun..

[35]  J. R. Wallis,et al.  Some long‐run properties of geophysical records , 1969 .

[36]  Mitsuru Nomura,et al.  Basic characteristics of variable rate video coding in ATM environment , 1989, IEEE J. Sel. Areas Commun..

[37]  Helmut Heeke Statistical multiplexing gain for variable bit rate video codecs in ATM networks , 1991 .

[38]  Duan-Shin Lee,et al.  TES Modeling for Analysis of a Video Multiplexer , 1992, Perform. Evaluation.

[39]  Ward Whitt,et al.  Squeezing the Most Out of ATM , 1995, IEEE Trans. Commun..

[40]  W. Feller The Asymptotic Distribution of the Range of Sums of Independent Random Variables , 1951 .

[41]  Gunnar Karlsson,et al.  Performance models of statistical multiplexing in packet video communications , 1988, IEEE Trans. Commun..

[42]  Gopalakrishnan Ramamurthy,et al.  Modeling and analysis of a variable bit rate video multiplexer , 1992, [Proceedings] IEEE INFOCOM '92: The Conference on Computer Communications.

[43]  H. E. Hurst,et al.  Long-Term Storage Capacity of Reservoirs , 1951 .

[44]  J. R. Wallis,et al.  Computer Experiments With Fractional Gaussian Noises: Part 1, Averages and Variances , 1969 .

[45]  Willem Verbiest,et al.  A variable bit rate video codec for asynchronous transfer mode networks , 1989, IEEE J. Sel. Areas Commun..

[46]  P. Glynn,et al.  Logarithmic asymptotics for steady-state tail probabilities in a single-server queue , 1994, Journal of Applied Probability.

[47]  Debasis Mitra,et al.  Effective bandwidth of general Markovian traffic sources and admission control of high speed networks , 1993, TNET.

[48]  A. I. McLeod,et al.  Fractional time series modelling , 1986 .

[49]  R. Dahlhaus Efficient parameter estimation for self-similar processes , 1989, math/0607078.

[50]  J. Hosking Modeling persistence in hydrological time series using fractional differencing , 1984 .

[51]  J. Beran Statistical methods for data with long-range dependence , 1992 .