Paper
27 December 1999 Characterizing user access to videos on the World Wide Web
Soam Acharya, Brian C. Smith, Peter Parnes
Author Affiliations +
Proceedings Volume 3969, Multimedia Computing and Networking 2000; (1999) https://doi.org/10.1117/12.373516
Event: Electronic Imaging, 2000, San Jose, CA, United States
Abstract
Despite evidence of rising popularity of video on the web (or VOW), little is known about how users access video. However, such a characterization can greatly benefit the design of multimedia systems such as web video proxies and VOW servers. Hence, this paper presents an analysis of trace data obtained from an ongoing VOW experiment in Lulea University of Technology, Sweden. This experiment is unique as video material is distributed over a high bandwidth network allowing users to make access decisions without the network being a major factor. Our analysis revealed a number of interesting discoveries regarding user VOW access. For example, accesses display high temporal locality: several requests for the same video title often occur within a short time span. Accesses also exhibited spatial locality of reference whereby a small number of machines accounted for a large number of overall requests. Another finding was a browsing pattern where users preview the initial portion of a video to find out if they are interested. If they like it, they continue watching, otherwise they halt it. This pattern suggests that caching the first several minutes of video data should prove effective. Lastly, the analysis shows that, contrary to previous studies, ranking of video titles by popularity did not fit a Zipfian distribution.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Soam Acharya, Brian C. Smith, and Peter Parnes "Characterizing user access to videos on the World Wide Web", Proc. SPIE 3969, Multimedia Computing and Networking 2000, (27 December 1999); https://doi.org/10.1117/12.373516
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Cited by 138 scholarly publications.
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KEYWORDS
Video

Internet

Multimedia

Calcium

Video compression

Factor analysis

Statistical analysis

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