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An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP

Published: 23 February 2011 Publication History

Abstract

Adaptive (video) streaming over HTTP is gradually being adopted, as it offers significant advantages in terms of both user-perceived quality and resource utilization for content and network service providers. In this paper, we focus on the rate-adaptation mechanisms of adaptive streaming and experimentally evaluate two major commercial players (Smooth Streaming, Netflix) and one open source player (OSMF). Our experiments cover three important operating conditions. First, how does an adaptive video player react to either persistent or short-term changes in the underlying network available bandwidth. Can the player quickly converge to the maximum sustainable bitrate? Second, what happens when two adaptive video players compete for available bandwidth in the bottleneck link? Can they share the resources in a stable and fair manner? And third, how does adaptive streaming perform with live content? Is the player able to sustain a short playback delay? We identify major differences between the three players, and significant inefficiencies in each of them.

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cover image ACM Conferences
MMSys '11: Proceedings of the second annual ACM conference on Multimedia systems
February 2011
294 pages
ISBN:9781450305181
DOI:10.1145/1943552
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 23 February 2011

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Author Tags

  1. adaptive streaming
  2. experimental evaluation
  3. rate adaptation algorithm
  4. video streaming over http

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MMSYS '11
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MMSYS '11: MMSYS '11 - Multimedia Systems Conference
February 23 - 25, 2011
CA, San Jose, USA

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Overall Acceptance Rate 176 of 530 submissions, 33%

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  • (2024)Enhancing Mobile Video Streaming through AMES-Cloud: A Cloud Computing Approach to Addressing Wireless Link Challenges2024 International Conference on Trends in Quantum Computing and Emerging Business Technologies10.1109/TQCEBT59414.2024.10545207(1-6)Online publication date: 22-Mar-2024
  • (2024)Real-EVE: Real-Time Edge-Assist Video Enhancement for Joint Denoising and Super-ResolutionAlgorithms and Architectures for Parallel Processing10.1007/978-981-97-0834-5_19(320-339)Online publication date: 12-Mar-2024
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