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RealTracer—Tools for Measuring the Performance of RealVideo on the Internet

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Abstract

The increase in high-bandwidth connections and high-speed computers has spurred the growth of streaming media across the Internet. While there have been a number of studies measuring the performance of traditional Internet traffic, there have not been sufficient empirical measurements ofvideo performance especially for commercial videos across the Internet. The lack of empirical workthat measures streaming video traffic may arise from the lack of effective video performance measurement tools. In this paper, we present RealTracer, a set of tools for measuring the performance of RealNetworks Video. RealTracer includes RealTracker, a customized video playe that plays RealNetworks Video from pre-selected playlist and records user-centric video performance information. RealTracer also includes RealData, a data analysis tool that helps manage,parse and analyze data captured by RealTracker. We describe the software architecture and usage ofRealTracker and the usage of RealData, both publicly available for download. To illustrate the useof RealTracer, we present some results from a study that used RealTracker to measure RealVideo performance across the Internet. Using RealData, that study made several contributions to better understanding the performance of streaming video on the Internet. Typical RealVideos have high quality, achieving an average frame rate of 10 frames per second and very smooth playout, but very few videos achieve full-motion frame rates. Overall video performance is most influenced by the bandwidth of the end-user connection to the Internet, but high-bandwidth Internet connections are pushing the video performance bottleneck closer to the server.

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References

  1. D. Cunningham and N. Francis, “An introduction to streaming video, cultivate interactive,” European Commission's Digital heritage and Cultural Content (DIGICULT), May 2001.

  2. M. Claypool and J. Riedl, “The effects of high-speed networks on multimedia jitter,” in Proc. of SCS Euromedia Conference (COMTEC), Munich, Germany, April 1999.

  3. M. Claypool and J. Tanner, “The effects of jitter on the perceptual quality of video,” in Proc. of the ACM Multimedia Conference, Orlando, Florida, USA, Vol. 2, November 1999.

  4. M. Chesire, A. Wolman, G. Voelker, and H. Levy, “Measurement and analysis of a streaming-media workload,” in Proc. of the 3rd USENIX Symposium on Internet Technologies and Systems (USITS), March 2001.

  5. A.C. Dalal and E. Perry, “A new architecture for measuring and assessing streaming media quality”, in Proc. of the Passive and Active Measurement Workshop (PAM), (Poster), La Jolla, California, April 2003

  6. J. Devore and R. Peck, Statistics — The Exploration and Analysis of Data, 2nd edition, Wadsworth, Inc., 1993.

  7. S. Floyd, M. Handley, J. Padhye and J. Widmer, “Equation-based congestion control for unicast applications,” in Proc. of ACM SIGCOMM Conference, 2000, pp. 45–58.

  8. Jupiter Media Metrix, “Users of media player applications increased 33 percent since last year, press release,” April 2001, available at http://www.jup.com/company/pressrelease-.jsp?doc=pr01040

  9. B. Krishnamurthy and C. Wills, “Analyzing factors that influence end-to-end web performance,” in Proc. of the Ninth International World Wide Web Conference, Amsterdam, Netherlands, May 2000.

  10. B. Krishnamurthy, C. Wills, and Y. Zhang, “On the use and performance of content distribution networks,” in Proc. of the ACM SIGCOMM Internet Measurement Workshop, San Francisco, California, USA, November 2001.

  11. D. Loguinov and H. Radha, “Measurement study of low-bitrate internet video streaming,” in Proc. of the ACM SIGCOMM Internet Measurement Workshop, San Francisco, California, USA, November 2001.

  12. B. Mah, “An empirical model of HTTP network traffic,” in Proc. of ACM SIGCOMM Conference, 1997, pp. 301–313.

  13. A. Mena and J. Heidemann, “An empirical study of real audio traffic,” in Proceedings of the IEEE Infocom, Tel-Aviv, Israel, March, 2000, pp. 101–110.

  14. V. Paxson,“End-to-end Internet packet dynamics,” IEEE/ACM Transactions on Networking, Vol. 7, No. 3, pp. 277–292, 1999.

    Article  Google Scholar 

  15. Real Networks Incorporated, RealProducer User's Guide, copyright 2000, available at http://www.service.real.com/help/library/guides/producerplus85/producer.htm

  16. Real Networks Incorporated, RealPlayer 8 User Manual, copyright 2000.

  17. R. Rejaie, M. Handley, and D. Estrin, “RAP: An end-to-end rate-based congestion control mechanism for realtime streams in the internet,” in proc. of IEEE INFOCOM conference, 1999.

  18. H. Schulzrinne, A. Rao, and R. Lanphier, “Real time streaming protocol (RTSP),” RFC 2326, April 1998, available at http://www.rfc-editor.org/rfc/rfc2326.txt

  19. H. Schulzrinne, S. Casner, R. Frederick, and V. Jacobson, “RTP: A transport protocol for real-time applications,” RFC 1889, January 1996, available at http://www.rfc-editor.org/rfc/rfc1889.txt.

  20. A. Tripathi and M. Claypool, “Improving multimedia streaming with content-aware video scaling,” in Proceedings of the Second International Workshop on Intelligent Multimedia Computing and Networking (IMMCN), Durham, North Carolina, USA, March 8–12, 2002

  21. K. Thompson, G. Miller and R. Wilder, “Wide-area internet traffic patterns and characteristics,” IEEE Network, Nov/Dec 1997.

  22. J.E. van der Merwe, R. Cáceres, Y.-H. Chu, and C.J. Sreenan, “mmdump—A tool for monitoring internet multimedia traffic,” ACM Computer Communication Review, Vol. 30, No. 4, 2000.

  23. E. Veloso, V. Almeida, W. Meira, A. Bestavros, and S. Jin, “A hierarchical characterization of a live streaming media workload,” in Proc. of the SIGCOMM Internet Measurement Workshop, Marseille, France, Nov 2002.

  24. Y. Wang, M. Claypool, and Z. Zuo, “An empirical study of RealVideo performance across the internet,” in Proc. of the ACM SIGCOMM Internet Measurement Workshop, San Francisco, California, USA, November 2001.

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Correspondence to Yubing Wang.

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Yubing Wang earned M.S. in Electrical Engineering from University of Science and Technology of China in 1993 and M.S. in Computer Science from WPI in 2001. He is currently working in EMC Corp. as a principal software engineer, participating in the developments of several EMC NAS products. He is also a Ph.D. candidate in Computer Science of WPI. His primary research interests include multimedia networking and distributed file system.

Mark Claypool earned M.S. and Ph.D. degrees from the University of Minnesota in 1993 and 1997, respectively. Dr. Claypool joined the Computer Science department of WPI in 1997, receiving tenure and promotion to Associate Professor in 2004. He is also the Director of the Interactive Media and Game Development major at WPI, a 4-year degree in the principles of interactive applications and computer-based game development. His primary research interests include multimedia networking, congestion control, and network games.

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Wang, Y., Claypool, M. RealTracer—Tools for Measuring the Performance of RealVideo on the Internet. Multimed Tools Appl 27, 411–430 (2005). https://doi.org/10.1007/s11042-005-3757-6

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