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Statistical analysis of H.264 video frame size distribution

Statistical analysis of H.264 video frame size distribution

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H.264 video traffic is expected to account for the majority of multimedia traffic to be carried in future heterogeneous networks. Modelling video frame sizes is highly useful in simulation studies, mathematical analysis and generating synthetic video traces for the purpose of testing and compliance. In this study, a statistical analysis is performed to determine an appropriate distribution of video frame sizes generated by the popular H.264 video codec. The study makes use of a number of real video traces with the goal of evaluating and fitting their frame sizes with well-known distributions. In the literature, it is reported that the Gamma and Weibull distributions give the best fit for frame sizes in the most popular video codecs including H.264. Our statistical analysis shows that both Gamma and Weibull distributions are very close to each other in terms of goodness-of-fit results and they give the best fit. The authors also show that the Inverse Gaussian distribution is ranked second after Gamma and Weibull distributions. Finally, they show that the distributions of Pearson Type V and Lognormal are ranked third and fourth in terms of goodness-of-fit.

References

    1. 1)
      • Auwera, G., David, P., Reisslein, M.: `Video traffic analysis of H.264/AVC and extensions: single layer statistics', Technical report, February 2007.
    2. 2)
      • Dai, M., Loguinov, D.: `Analysis and modeling of MPEG-4 and H.264 multi-layer video traffic', Proc. 24th Annual Joint Conf. IEEE Computer and Communications Societies (INFOCOM '05), March 2005, Miami, FL, USA, 4, p. 2257–2267.
    3. 3)
      • Ryu, B., Elwalid, A.: `The importance of long-range dependence of VBR video traffic in ATM traffic engineering: myths and realities', Proc. Conf. on Applications, Technologies, Architectures, and Protocols for Computer Communications, August 1996, California, USA, p. 3–14.
    4. 4)
    5. 5)
      • Reisslein, M., Lassetter, J., Ratman, S., Lotfallah, O., Fitzek, F., Panchanathan, S.: `Traffic and quality characterization of scalable encoded video: a large-scale trace-based study – part 1: overview and definitions', Technical report, December 2003.
    6. 6)
      • A. Law , W. Kelton . (1999) Simulation modeling and analysis.
    7. 7)
      • Koumaras, H., Skianis, C., Gardikis, G., Kourtis, A.: `Analysis of H.264 video encoded traffic', INC 2005 Fifth Int. Network Conf., July 2005, Samos Island, Greece.
    8. 8)
      • B. Ryu . Modeling and simulation of broadband satellite networks – Part II: traffic modeling. IEEE Commun. Mag. , 72 - 79
    9. 9)
      • Domoxoudis, S., Kouremenos, S., Drigas, A., Loumos, V.: `Frame-based modeling of H264 constrained videoconference traffic over an IP commercial platform', Proc. IEEE Second Int. Conf. on Testbeds & Research Infrastructures for the Development of Networks and Communities, July 2006, p. 6–221.
    10. 10)
      • Bock, R.K.: http://rkb.home.cern.ch/rkb/AN16pp/node143.html.
    11. 11)
      • K. Levenberg . A method for the solution of certain non-linear problems in least squares. Q. Appl. Math. , 2 , 164 - 168
    12. 12)
      • Heyman, D.P., Lakshman, T.V., Tabatabai, A., Heeke, H.: `Modeling teleconference traffic from VBR video coders', Proc. IEEE Int. Conf. on Communications (ICC'94), May 1994, New Orleans, LA, USA, p. 1744–1748.
    13. 13)
    14. 14)
      • Polycom PVX, http://www.polycom.com.
    15. 15)
    16. 16)
    17. 17)
    18. 18)
    19. 19)
    20. 20)
      • Krunz, M., Hughes, H.: `A traffic model for MPEG-Coded VBR streams', Proc. ACM SIGMETRICS Conf., 1995, p. 47–55.
    21. 21)
      • D.E. Knuth . (1998) The art of computer programming – seminumerical algorithms.
    22. 22)
    23. 23)
    24. 24)
      • VCON Vpoint HD, http://www.vcon.com.
    25. 25)
    26. 26)
      • Dai, M., Zhang, Y., Loguinov, D.: `A unified traffic model for MPEG-4 and H.264 video traces', Presented at IEEE Transactions on Multimedia, 2009, p. 1010–1023.
    27. 27)
      • ‘H.264/AVC video trace library’, available at: http://trace.eas.asu.edu.
    28. 28)
      • G.V. Auwera , P.T. David , M. Reisslein . Traffic characteristics of H.264/AVC variable bit rate video. IEEE Commun. Mag. , 11 , 698 - 718
    29. 29)
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