Supporting stored video: Reducing rate variability and end-to-end resource requirements through optimal smoothing

James D. Salehi, Zhi Li Zhang, James F. Kurose, Don Towsley

Research output: Contribution to journalArticle

88 Scopus citations

Abstract

VBR compressed video is known to exhibit significant, multiple-time-scale bit rate variability. In this paper, we consider the transmission of stored video from a server to a client across a high speed network, and explore how the client buffer space can be used most effectively toward reducing the variability of the transmitted bit rate. We present two basic results. First, we present an optimal smoothing algorithm for achieving the greatest possible reduction in rate variability when transmitting stored video to a client with given buffer size. We provide a formal proof of optimality, and demonstrate the performance of the algorithm on a set of long MPEG-1 encoded video traces. Second, we evaluate the impact of optimal smoothing on the network resources needed for video transport, under two network service models: Deterministic Guaranteed service [1, 9] and Renegotiated CBR (RCBR) service [8, 7]. Under both models, we find the impact of optimal smoothing to be dramatic.

Original languageEnglish (US)
Pages (from-to)222-231
Number of pages10
JournalPerformance Evaluation Review
Volume24
Issue number1
DOIs
StatePublished - May 1996

Fingerprint Dive into the research topics of 'Supporting stored video: Reducing rate variability and end-to-end resource requirements through optimal smoothing'. Together they form a unique fingerprint.

  • Cite this