A "GAP-Model" based Framework for Online VVoIP QoE Measurement

  • Published : 2007.12.31

Abstract

Increased access to broadband networks has led to a fast-growing demand for voice and video over IP(VVoIP) applications such as Internet telephony(VoIP), videoconferencing, and IP television(IPTV). For pro-active troubleshooting of VVoIP performance bottlenecks that manifest to end-users as performance impairments such as video frame freezing and voice dropouts, network operators cannot rely on actual end-users to report their subjective quality of experience(QoE). Hence, automated and objective techniques that provide real-time or online VVoIP QoE estimates are vital. Objective techniques developed to-date estimate VVoIP QoE by performing frame-to-frame peak-signal-to-noise ratio(PSNR) comparisons of the original video sequence and the reconstructed video sequence obtained from the sender-side and receiver-side, respectively. Since processing such video sequences is time consuming and computationally intensive, existing objective techniques cannot provide online VVoIP QoE. In this paper, we present a novel framework that can provide online estimates of VVoIP QoE on network paths without end-user involvement and without requiring any video sequences. The framework features the "GAP-model", which is an offline model of QoE expressed as a function of measurable network factors such as bandwidth, delay, jitter, and loss. Using the GAP-model, our online framework can produce VVoIP QoE estimates in terms of "Good", "Acceptable", or "Poor"(GAP) grades of perceptual quality solely from the online measured network conditions.

Keywords

References

  1. J. Klaue, B. Rathke, and A. Wolisz, 'EvalVid - A Framework for Video Transmission and Quality Evaluation,' in Proc. Conf. Modeling Techniques and Tools for Computer Performance Evaluation, 2003
  2. ITU-T Recommendation J.144, 'Objective perceptual video quality measurement techniques for digital cable television in the presence of a full reference,' 2001
  3. A. Watson and M. A. Sasse, 'Measuring perceived quality of speech and video in multimedia conferencing applications,' in Proc. ACM Multimedia, Sept. 1998, pp. 55-60
  4. R. Steinmetz, 'Human perception of jitter and media synchronization,' IEEE J. Sel. Areas Commun., pp. 61-72, vol. 14, no. 1, pp. 61-72, Jan. 1996 https://doi.org/10.1109/49.481694
  5. P. Calyam, M. Haffner, E. Ekici, and C.-G. Lee, 'Measuring interaction QoE in internet videoconferencing,' in Proc. IFlP/IEEE MMNS, Oct. 2007, pp. 14-25
  6. ITU-T Recommendation G.107, 'The E-model: A computational model for use in transmission planning,' 1998
  7. ITU-T Recommendation P.862, 'Perceptual evaluation of speech quality (PESQ): An objective method for end-to-end speech quality assessment of narrowband telephone networks and speech codecs,' 2001
  8. A. Markopoulou, F. Tobagi, and M. Karam, 'Assessment of VoIP quality over Internet backbones,' in Proc. IEEE INFOCOM, June 2002, pp. 150-159
  9. S. Mohamed, G. Rubino, and M. Varela, 'A method for quantitative evaluation of audio quality over packet networks and its comparison with existing techniques,' in Proc. MESAQUlN, 2004
  10. Telchemy VQMon. [Online]. Available: http://www.telchemy.com
  11. P. Calyam, W. Mandrawa, M. Sridharan, A. Khan, and P. Schopis, 'H.323 beacon: An H.323 application related end-to-end performance troubleshooting tool,' in Proc. ACM SIGCOMM NetTs, Sept. 2004, pp. 241-246
  12. S. Winkler, Digital Video Quality: Vision Models and Metrics. John Wiley and Sons Publication, 2005
  13. O. Nemethova, M. Ries, E. Siffel, and M. Rupp, 'Quality assessment for H.264 coded low-rate low-resolution video sequences,' in Proc. Conf. Internet and Information Technologies, 2004
  14. Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, 'Image quality assessment: From error visibility to structural similarity,' IEEE Trans. Image Processing, vol. 13, no. 4, pp. 600-612, Apr. 2004 https://doi.org/10.1109/TIP.2003.819861
  15. K. T. Tan and M. Ghanbari, 'A Combinational automated MPEG video quality assessment model', in Proc. Conf. Image Processing and its Application, July 1999, pp. 188-192
  16. ANSI TI.801.03 Standard, 'Digital transport of one-way video signals Parameters for objective performance assessment,' 2003
  17. S. Tao, J. Apostolopoulos, and R. Guerin, 'Real-time monitoring of video quality in IP networks,' in Proc. ACM NOSSDAV, June 2005, pp. 129-134
  18. F. Massidda, D. Giusto, and C. Perra, 'No reference video quality estimation based on human visual system for 2.5/3G devices,' in Proc. the SPIE, Mar. 2005, pp. 168-179
  19. S. Mohamed and G. Rubino, 'A study of real-time packet video quality using random neural networks,' IEEE Trans. Circ. Sys. for Video Tech., vol. 12, no. 12, pp. 1071-1083, Dec. 2002 https://doi.org/10.1109/TCSVT.2002.806808
  20. 'The video development initiative (ViDe) videoconferencing cookbook,' [Online]. Available: http://www.vide.net/cookbook
  21. H. Tang and L. Duan, J. Li, 'A performance monitoring architecture for IP videoconferencing,' in Proc. Workshop on IP Operations and Management, Oct. 2004, pp. 48-54
  22. 'Implementing QoS solutions for H.323 videoconferencing over IP,' Cisco Systems Technical Whitepaper Document Id: 21662, 2007
  23. ITU-T Recommendation G.114, 'One-way transmission time,' 1996
  24. P. Calyam, M. Sridharan, W. Mandrawa, and P. Schopis, 'Performance measurement and analysis of H.323 traffic,' in Proc. Passive and Active Measurement Workshop, Apr. 2004, pp. 137-146
  25. M. Claypool and J. Tanner, 'The effects of jitter on the perceptual quality of video,' in Proc. ACM Multimedia, Nov. 1999
  26. NISTnet Network Emulator. [Online]. Available: http://snad.ncsl.nist.gov /itg/nistnet
  27. H. R. Wu, T. Ferguson, and B. Qiu, 'Digital video quality evaluation using quantitative quality metrics,' in Proc. Int. Conf. on Signal Processing, Oct. 1998, pp. 1013-1016
  28. A. Tirumala, L. Cottrell, and T. Dunigan, 'Measuring end-to-end bandwidth with Iperf using Web100,' in Proc. Passive and Active Measurement Workshop, 2003
  29. ITU-T Recommendation P.911, 'Subjective audiovisual quality assessment methods for multimedia applications,' 1998
  30. ITU-T Recommendation P.920, 'Interactive test methods for audiovisual communications,' 2000
  31. ITU-T Recommendation BT.500-1O, 'Methodology for the subjective assessment of quality of television pictures,' 2000
  32. M. Pinson and S. Wolf, 'A new standardized method for objectively measuring video quality,' IEEE Trans. Broadcasting, vol. 50, no. 3, pp. 312-322, Sept. 2004 https://doi.org/10.1109/TBC.2004.834028
  33. C. Lambrecht, D. Constantini, G. Sicuranza, and M. Kunt, 'Quality assessment of motion rendition in video coding,' IEEE Trans. Circ. Sys. for Video Tech., vol. 9, no. 5, pp. 766-782, Aug. 1999 https://doi.org/10.1109/76.780365