Workload generation for YouTube |
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Authors: | Abdolreza Abhari Mojgan Soraya |
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Affiliation: | (1) Computer Science Department, Ryerson University, Toronto, ON, M5B 2K3, Canada;(2) Electrical Engineering Department, Ryerson University, Toronto, ON, M5B 2K3, Canada |
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Abstract: | This paper introduces a workload characterization study of the most popular short video sharing service of Web 2.0, YouTube.
Based on a vast amount of data gathered in a five-month period, we analyzed characteristics of around 250,000 YouTube popular
and regular videos. In particular, we collected lists of related videos for each video clip recursively and analyzed their
statistical behavior. Understanding YouTube traffic and similar Web 2.0 video sharing sites is crucial to develop synthetic
workload generators. Workload simulators are required for evaluating the methods addressing the problems of high bandwidth
usage and scalability of Web 2.0 sites such as YouTube. The distribution models, in particular Zipf-like behavior of YouTube
popular video files suggests proxy caching of YouTube popular videos can reduce network traffic and increase scalability of
YouTube Web site. YouTube workload characteristics provided in this work enabled us to develop a workload generator to evaluate
the effectiveness of this approach. |
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Keywords: | |
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