Statistical buffering for streaming media data access in a mobile environment

Jian Zhai, Xiang Li, Qing Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


Streaming media (e.g., music or video) data access has been a research problem over the past few years, and the problem becomes tougher when the clients are mobile devices whose limited storage spaces prevent the clients from holding a large cache. A practical solution for the cellular system is to buffer the streaming data on the base stations, serving as the "cache" to the mobile devices. However, when mobile devices move from one cell to another, the cached data should also be migrated to the corresponding base station in order that users can view the media smoothly. When the number of requests increases, stations may face heavy data migration and storage burden. In this paper, we propose a statistical buffering mechanism by adapting SAA search which makes use of prior knowledge (statistical data) to predict the trend of user movement among cells. Experimental studies show that, with an acceptable complexity, our algorithms can obtain good performance on buffering streaming media data.

Original languageEnglish
Title of host publicationApplied Computing 2006 - The 21st Annual ACM Symposium on Applied Computing - Proceedings of the 2006 ACM Symposium on Applied Computing
Number of pages5
Publication statusPublished - 21 Nov 2006
Externally publishedYes
Event2006 ACM Symposium on Applied Computing - Dijon, France
Duration: 23 Apr 200627 Apr 2006

Publication series

NameProceedings of the ACM Symposium on Applied Computing


Conference2006 ACM Symposium on Applied Computing


  • Mobile
  • Statistical buffering
  • Streaming

ASJC Scopus subject areas

  • Software


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