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An Empirical Study of a Segment-Based Streaming Proxy in an Enterprise Environment

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Web Content Caching and Distribution (WCW 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3293))

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Abstract

Streaming media workloads have a number of desirable properties that make them good candidates for caching via proxy systems. The content does not get modified, and access patterns exhibit some locality of reference. However, media files tend to be much larger in size than traditional web pages, and users tend to view video clips only partially. Hence, segment-based strategies have been proposed to deliver large streaming media objects via a web-proxy. In this work, we evaluate the performance of such a segment-based streaming proxy using extensive trace driven simulation. We use representative workloads from enterprise media server logs, and evaluate the caching system performance regarding different cache sizes, different segment sizes, and different prefetching methods. Our results show that cost-effective caching requires only about 8 – 16 % of the total unique object size as proxy storage. Secondly, a segment size of around 200 Kbytes provides a good trade-off between cache object granularity and transaction overhead. Finally, a lazier prefetching schedule that provides a half-segment look-ahead has a significant performance gain when compared to a more aggressive one-segment look-ahead scheme.

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© 2004 Springer-Verlag Berlin Heidelberg

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Roy, S., Shen, B., Chen, S., Zhang, X. (2004). An Empirical Study of a Segment-Based Streaming Proxy in an Enterprise Environment. In: Chi, CH., van Steen, M., Wills, C. (eds) Web Content Caching and Distribution. WCW 2004. Lecture Notes in Computer Science, vol 3293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30471-5_20

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  • DOI: https://doi.org/10.1007/978-3-540-30471-5_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23516-3

  • Online ISBN: 978-3-540-30471-5

  • eBook Packages: Springer Book Archive

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