This paper presents modelling results for H.26x video traffic generated by popular videoconference software applications. The analysis of videoconference data, that were measured during realistic point-point videoconference sessions, led us to the general conclusion that the traffic can be distinguished into two categories: unconstrained and constrained. In the unconstrained traffic, there is a direct relation between the encoder and the form of the frequency histogram of the frame-size sequence. Moreover, for this type of traffic, strong correlations between successive video frames can be found. On the other hand, where bandwidth constraints are imposed during the encoding process, the generated traffic appears to exhibit similar characteristics for all the examined encoders with the very low autocorrelation values being the most notable one. On the basis of these results, this study proposes methods to calculate the parameters of a widely adopted autoregressive model for both types of traffic. 1. Introduction H.26x videoconference traffic is expected to account for large portions of the multimedia traffic in future heterogeneous networks (wire, wireless and satellite). The videoconference traffic models for these networks must cover a wide range of traffic types and characteristics because the type of the terminals will range from a single home or mobile user (low video bit rate), where constrained video traffic is mainly produced, to a terminal connected to a backbone network (high video bit rate), where the traffic is presented to be unconstrained. Partly due to the above reasons, the modelling and performance evaluation of videoconference traffic has been extensively studied in literature and a wide range of modelling methods exist. The results of relevant early studies [1–8] concerning the statistical analysis of variable bit rate videoconference streams being multiplexed in ATM networks, indicate that the histogram of the videoconference frame-size sequence exhibits an asymmetric bell shape and that the autocorrelation function decays approximately exponentially to zero. An important body of knowledge, in videoconference traffic modelling, is the approach in [5] where the DAR [9] model was proposed. More explicitly, in this study, the authors noted that AR models of at least order two are required for a satisfactory modelling of the examined H.261 encoded traffic patterns. However, in the same study, the authors observed that a simple DAR model, based on a discrete-time, discrete state Markov Chain performs better—with respect to queueing—than a
References
[1]
B. Maglaris, D. Anastassiou, P. Sen, G. Karlsson, and J. D. Robbins, “Performance models of statistical multiplexing in packet video communications,” IEEE Transactions on Communications, vol. 36, no. 7, pp. 834–843, 1988.
[2]
R. Kishimoto, Y. Ogata, and F. Inumara, “Generation interval distribution characteristics of packetized variable rate video coding data streams in an ATM network,” IEEE Journal on Selected Areas in Communications, vol. 7, no. 5, pp. 833–841, 1989.
[3]
H. S. Chin, J. W. Goodge, R. Griffiths, and D. J. Parish, “Statistics of video signals for viewphone-type pictures,” IEEE Journal on Selected Areas in Communications, vol. 7, no. 5, pp. 826–832, 1989.
[4]
M. Nomura, T. Fujii, and N. Ohta, “Basic characteristics of variable rate video coding in ATM environment,” IEEE Journal on Selected Areas in Communications, vol. 7, no. 5, pp. 752–760, 1989.
[5]
D. P. Heyman, A. Tabatabai, and T. V. Lakshman, “Statistical analysis and simulation study of video teleconference traffic in ATM networks,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 2, no. 1, pp. 49–59, 1992.
[6]
D. M. Cohen and D. P. Heyman, “Performance modeling of video teleconferencing in ATM networks,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 3, no. 6, pp. 408–422, 1993.
[7]
D. Heyman and T. V. Lakshman, “Modeling teleconference traffic from VBR video coders,” in Proceedings of the IEEE International Conference on Communications, pp. 1744–1748, May 1994.
[8]
D. M. Lucantoni and M. F. Neuts, “Methods for performance evaluation of VBR video traffic models,” IEEE/ACM Transactions on Networking, vol. 2, no. 2, pp. 176–180, 1994.
[9]
P. A. Jacobs and P. A. W. Lewis, “Time series generated by mixtures,” Journal of Time Series Analysis, vol. 4, no. 1, pp. 19–36, 1983.
[10]
A. Elwalid, D. Heyman, T. V. Lakshman, D. Mitra, and A. Weiss, “Fundamental bounds and approximations for ATM multiplexers with applications to video teleconferencing,” IEEE Journal on Selected Areas in Communications, vol. 13, no. 6, pp. 1004–1016, 1995.
[11]
D. P. Heyman, “The GBAR source model for VBR videoconferences,” IEEE/ACM Transactions on Networking, vol. 5, no. 4, pp. 554–560, 1997.
[12]
R. Bo, “Modeling and simulation of broadband satellite networks—part II: traffic modeling,” IEEE Communications Magazine, vol. 37, no. 7, pp. 48–56, 1999.
[13]
A. Erramilli, O. Narayan, and W. Willinger, “Experimental queueing analysis with long-range dependent packet traffic,” IEEE/ACM Transactions on Networking, vol. 4, no. 2, pp. 209–223, 1996.
[14]
G. Sisodia, L. Guan, M. Hedley, and S. De, “A new modeling approach of H.263+ VBR coded video sources in ATM networks,” Real-Time Imaging, vol. 6, no. 5, pp. 347–357, 2000.
[15]
K. Dolzer and W. Payer, “On aggregation strategies for multimedia traffic,” in Proceedings of the 1st Polish-German Teletraffic Symposium (PGTS '00), Dresden, Germany, September 2000.
[16]
W. C. Poon and K. T. Lo, “A refined version of M/G/∞ processes for modelling VBR video traffic,” Computer Communications, vol. 24, no. 11, pp. 1105–1114, 2001.
[17]
L. Yan-ling, W. Peng, and W. Wei-ling, “A steady source model for VBR video conferences,” in Proceedings of the International Conference on Information Technology: Computers and Communications, Las Vegas, Nev, USA, 2003.
[18]
A. Lazaris, P. Koutsakis, and M. Paterakis, “A new model for video traffic originating from multiplexed MPEG-4 videoconference streams,” Performance Evaluation, vol. 65, no. 1, pp. 51–70, 2007.
[19]
F. H. P. Fitzek and M. Reisslein, “MPEG-4 and H.263 video traces for network performance evaluation,” IEEE Network, vol. 15, no. 6, pp. 40–54, 2001.
[20]
C. Skianis, K. Kontovasilis, A. Drigas, and M. Moatsos, “Measurement and statistical analysis of asymmetric multipoint videoconference traffic in IP networks,” Telecommunication Systems, vol. 23, no. 1-2, pp. 95–122, 2003.
[21]
ITU Recommendation, H.261: Video Codec for Audiovisual Services at 64？Kbit/s, 1993.
[22]
ITU Recommendation, H.263: Video Coding for Low Bit Rate Communication, 2005.
[23]
H.263 Standard, Overview and TMS320C6x Implementation, White Paper, http://www.ubvideo.com.
[24]
ITU Recommendation, H.264: Advanced Video Coding for Generic Audiovisual Services, 2007.
[25]
R. Frederick, Experiences With Real-Time Software Video Compression, Xerox Parc, 1994.
[26]
S. Domoxoudis, S. Kouremenos, V. Loumos, and A. Drigas, “Measurement, modelling and simulation of videoconference traffic from VBR video encoders,” in Proceedings of the 2nd International Working Conference on the Performance Modelling and Evaluation of Heterogeneous Networks (HET-NETs '04), Ilkley, West Yorkshire, UK, July 2004.
[27]
The ViC Tool, http://www-mice.cs.ucl.ac.uk/multimedia/software/vic.
[28]
VCON Vpoint HD, http://www.vcon.com.
[29]
Polycom PVX, http://www.polycom.com.
[30]
France Telecom eConf, http://www.rd.francetelecom.com.
[31]
Sorenson EnVision, http://www.sorensonvrs.com.
[32]
S. Domoxoudis, S. Kouremenos, A. Drigas, and V. Loumos, “Frame-based modeling of H.264 constrained videoconference traffic over an IP commercial platform,” in Proceedings of the 2nd International IEEE/Create-Net Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities, pp. 216–221, Barcelona, Spain, March 2006.
[33]
OpenH323 Project, http://openh323.org.
[34]
S. R. McCanne, “Scalable compression and transmission of internet multicast video,” Tech. Rep. UCB/CSD-96-928, Computer Science Division (EECS), University of California, Berkeley, Calif, USA, 1996, 94720.
[35]
L. D. McMahan, Video conferencing over an ATM network [thesis], California State University, Northridge, Calif, USA, 1997.
[36]
MorningSound, http://www.soundmorning.com/.
[37]
T. V. Lakshman, A. Ortega, and A. R. Reibman, “VBR video: tradeoffs and potentials,” Proceedings of the IEEE, vol. 86, no. 5, pp. 952–972, 1998.
