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

James D. Salehi; Zhi Li Zhang; Jim Kurose; Don Towsley

doi:10.1109/90.720873

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

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

Computer Science and Engineering

Research output: Contribution to journal › Article › peer-review

229 Scopus citations

Abstract

Variable-bit-rate (VBR) compressed video can 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 network, and explore how the client buffer space can be used most effectively toward reducing the variability of the transmitted bit rate. Two basic results are presented. First, we show how to achieve the greatest possible reduction in rate variability when sending stored video to a client with given buffer size. We formally establish the optimality of our approach and illustrate its performance over 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], [31] and renegotiated constant-bit-rate (RCBR) service [9]. Under both models, the impact of optimal smoothing is dramatic.

Original language	English (US)
Pages (from-to)	397-410
Number of pages	14
Journal	IEEE/ACM Transactions on Networking
Volume	6
Issue number	4
DOIs	https://doi.org/10.1109/90.720873
State	Published - 1998

Bibliographical note

Funding Information:
Manuscript received July 22, 1996; revised February 19, 1998; approved by IEEE/ACM TRANSACTIONS ON NETWORKING Editor J. Bolot. This work was supported by the National Science Foundation under Grant NCR-9206908, Grant CDA-9502639, and Grant CCR-9119922, and by the Advanced Research Projects Agency under ESD/AVS Contract F-19628-92-C-0089. J. D. Salehi is at 2025 W. Middlefield Rd., Mountain View, CA 94040 USA (e-mail: jim_salehi@yahoo.com). Z.-L. Zhang is with the Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455 USA. J. Kurose and D. Towsley are with the Department of Computer Science, University of Massachusetts, Amherst, MA 01003-4610 USA. Publisher Item Identifier S 1063-6692(98)06689-8.

Keywords

Computer network performance
Computer networks
Interactive TV
Multimedia communication
Multimedia systems
Network operating systems
Network servers

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10.1109/90.720873

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

abstract = "Variable-bit-rate (VBR) compressed video can 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 network, and explore how the client buffer space can be used most effectively toward reducing the variability of the transmitted bit rate. Two basic results are presented. First, we show how to achieve the greatest possible reduction in rate variability when sending stored video to a client with given buffer size. We formally establish the optimality of our approach and illustrate its performance over 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], [31] and renegotiated constant-bit-rate (RCBR) service [9]. Under both models, the impact of optimal smoothing is dramatic.",

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note = "Funding Information: Manuscript received July 22, 1996; revised February 19, 1998; approved by IEEE/ACM TRANSACTIONS ON NETWORKING Editor J. Bolot. This work was supported by the National Science Foundation under Grant NCR-9206908, Grant CDA-9502639, and Grant CCR-9119922, and by the Advanced Research Projects Agency under ESD/AVS Contract F-19628-92-C-0089. J. D. Salehi is at 2025 W. Middlefield Rd., Mountain View, CA 94040 USA (e-mail: jim_salehi@yahoo.com). Z.-L. Zhang is with the Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455 USA. J. Kurose and D. Towsley are with the Department of Computer Science, University of Massachusetts, Amherst, MA 01003-4610 USA. Publisher Item Identifier S 1063-6692(98)06689-8.",

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

Abstract

Bibliographical note

Keywords

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