Stochastic fluid theory for P2P streaming systems

Rakesh Kumar, Yong Liu, Keith Ross

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We develop a simple stochastic fluid model that seeks to expose the fundamental characteristics and limitations of P2P streaming systems. This model accounts for many of the essential features of a P2P streaming system, including the peers' real-time demand for content, peer churn (peers joining and leaving), peers with heterogeneous upload capacity, limited infrastructure capacity, and peer buffering and playback delay. The model is tractable, providing closed-form expressions which can be used to shed insight on the fundamental behavior of P2P streaming systems. The model shows that performance is largely determined by a critical value. When the system is of moderate-to-large size, if a certain ratio of traffic loads exceeds the critical value, the system performs well; otherwise, the system performs poorly. Furthermore, large systems have better performance than small systems since they are more resilient to bandwidth fluctuations caused by peer churn. Finally, buffering can dramatically improve performance in the critical region, for both small and large systems. In particular, buffering can bring more improvement than can additional infrastructure bandwidth.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE INFOCOM 2007
Subtitle of host publication26th IEEE International Conference on Computer Communications
Number of pages9
StatePublished - 2007
EventIEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications - Anchorage, AK, United States
Duration: May 6 2007May 12 2007

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


OtherIEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications
Country/TerritoryUnited States
CityAnchorage, AK

ASJC Scopus subject areas

  • General Computer Science
  • Electrical and Electronic Engineering


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