Watching user generated videos with prefetching

  • Authors:

  • Samamon Khemmarat;Renjie Zhou;Lixin Gao;Michael Zink

  • Affiliations:

  • University of Massachusetts, Amherst, MA, USA;Harbin Engineering University, Harbin, China;University of Massachusetts, Amherst, MA, USA;University of Massachusetts, Amherst, MA, USA

  • Venue:
  • MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems
  • Year:
  • 2011

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Abstract

Even though user generated video sharing sites are tremendously popular, the experience of the user watching videos is often unsatisfactory. Delays due to buffering before and during a video playback at a client are quite common. In this paper, we present a prefetching approach for user-generated video sharing sites like YouTube. We motivate the need for prefetching by showing that video playbacks of videos of YouTube is often unsatisfactory and introduce a series of prefetching schemes: the conventional caching scheme, the search result-based prefetching scheme, and the recommendation-aware prefetching scheme. We evaluate and compare the proposed schemes using user browsing pattern data collected from network measurement. We find that the recommendation-aware prefetching approach can achieve an overall hit ratio up to 81%, while the hit ratio achieved by the caching scheme can only reach 40%. Thus, the recommendation-aware prefetching approach demonstrates a strong potential for improving the playback quality at the client. We also explore the trade-offs and feasibility of implementing recommendation-aware prefetching.