JOURNAL ARTICLE

Adaptive rate control for streaming stored fine-grained scalable video

Abstract

In this paper we investigate adaptive streaming of stored fine-grained scalable video over a TCP-friendly connection. The goal is to develop low-complexity yet high-performing schemes that adequately adapt to the short- and long-term variations in available bandwidth. We first present a novel framework for low-complexity streaming of fine-grained scalable video over a TCP-friendly connection. In the context of this scheme, and under the assumption of complete knowledge of bandwidth evolution, we derive an optimal policy for a criterion that involves both image quality and quality variability during playback. Based on this ideal optimal policy, we develop a real-time heuristic to stream fine-grained scalable video over the Internet, and we study its performance using real Internet traces. We find that our heuristic policy performs almost as well as the ideal optimal policy for a wide-range of bandwidth scenarios and when run over ordinary TCP the policy is essentially as good as when running the policy over popular TCP-friendly algorithms.

Keywords:
Computer science Scalability Bandwidth (computing) Heuristic The Internet Real-time computing Computer network Quality of service Distributed computing Context (archaeology) Artificial intelligence Operating system

Metrics

78
Cited By
7.67
FWCI (Field Weighted Citation Impact)
18
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Network Traffic and Congestion Control
Physical Sciences →  Computer Science →  Computer Networks and Communications
Peer-to-Peer Network Technologies
Physical Sciences →  Computer Science →  Computer Networks and Communications
Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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