Reducing data request contentions for improved streaming quality

  • Authors:
  • Yao Liu;Fei Li;Lei Guo;Songqing Chen

  • Affiliations:
  • George Mason University, Fairfax, VA, USA;George Mason University, Fairfax, VA, USA;Yahoo! Inc., Sunnyvale, CA, USA;George Mason University, Fairfax, VA, USA

  • Venue:
  • Proceedings of the 20th international workshop on Network and operating systems support for digital audio and video
  • Year:
  • 2010

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Abstract

In P2P assisted multi-channel live streaming systems, it is commonly believed that in unpopular channels, quality degradation is due to the small number of participating peers with almost-the-same set of available data; this phenomena prevents effective data exchanges among peers themselves and automatically leads to data request contentions once a new data chunk becomes available. In popular programs, our measurement on PPLive for a continuous three-month period at various locations also shows numerous occurrences of quality degradation because of the even higher ratio (up to 190%) of repetitive data requests for the same data chunks. These results motivate us to investigate effective data ex- change strategies to reduce data request contentions for im- proved streaming quality. IDEA, an Improved peer Data Exchange Algorithm, is proposed to carefully select chunks to request from different peers. We conduct extensive sim- ulations and the results show that IDEA significantly out- performs the widely used algorithms in deployed systems.