Statistical analysis of H.264 video frame size distribution

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.

[1]  Martin Reisslein,et al.  MPEG-4 and H.263 video traces for network performance evaluation , 2001, IEEE Netw..

[2]  Athanasios Drigas,et al.  Frame-based modeling of H.264 constrained videoconference traffic over an IP commercial platform , 2006, 2nd International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities, 2006. TRIDENTCOM 2006..

[3]  Kwok-Tung Lo,et al.  A refined version of M/G/∞ processes for modelling VBR video traffic , 2001, Comput. Commun..

[4]  D. Kundu,et al.  Theory & Methods: Generalized exponential distributions , 1999 .

[5]  Anwar Elwalid,et al.  The Importance of Long-Range Dependence of VBR Video Traffic in ATM Traffic Engineering: Myths and Realities , 1996, SIGCOMM.

[6]  Marwan Krunz,et al.  A traffic for MPEG-coded VBR streams , 1995, SIGMETRICS '95/PERFORMANCE '95.

[7]  S. Panchanathan,et al.  Traffic and Quality Characterization of Scalable Encoded Video : A Large – Scale Trace – Based Study Part 1 : Overview and Definitions ∗ † , 2002 .

[8]  Dmitri Loguinov,et al.  Analysis and modeling of MPEG-4 and H.264 multi-layer video traffic , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[9]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[10]  Walter Willinger,et al.  Long-range dependence in variable-bit-rate video traffic , 1995, IEEE Trans. Commun..

[11]  Heiko Schwarz,et al.  Overview of the Scalable Video Coding Extension of the H.264/AVC Standard , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[12]  Aggelos Lazaris,et al.  Modeling multiplexed traffic from H.264/AVC videoconference streams , 2010, Comput. Commun..

[13]  Donald E. Knuth,et al.  The art of computer programming. Vol.2: Seminumerical algorithms , 1981 .

[14]  Dmitri Loguinov,et al.  A Unified Traffic Model for MPEG-4 and H.264 Video Traces , 2009, IEEE Transactions on Multimedia.

[15]  Aggelos Lazaris,et al.  A new model for video traffic originating from multiplexed MPEG-4 videoconference streams , 2008, Perform. Evaluation.

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

[17]  Kenneth Levenberg A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[18]  T. V. Lakshman,et al.  Modeling teleconference traffic from VBR video coders , 1994, Proceedings of ICC/SUPERCOMM'94 - 1994 International Conference on Communications.

[19]  Martin Reisslein,et al.  Traffic and Quality Characterization of Single-Layer Video Streams Encoded with the H.264/MPEG-4 Advanced Video Coding Standard and Scalable Video Coding Extension , 2008, IEEE Transactions on Broadcasting.

[20]  Bo Ryu,et al.  Modeling and simulation of broadband satellite networks. II. Traffic modeling , 1999, IEEE Commun. Mag..

[21]  Donald E. Knuth The Art of Computer Programming 2 / Seminumerical Algorithms , 1971 .

[22]  Debasis Kundu,et al.  Generalized exponential distribution: different method of estimations , 2001 .

[23]  Shugong Xu,et al.  A gamma autoregressive video model on ATM networks , 1998, IEEE Trans. Circuits Syst. Video Technol..

[24]  Dilip Sarkar,et al.  Modeling full-length video using Markov-modulated gamma-based framework , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).