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A Video Bitrate Adaptation and Prediction Mechanism for HTTP Adaptive Streaming

A Video Bitrate Adaptation and Prediction Mechanism for HTTP Adaptive Streaming A Video Bitrate Adaptation and Prediction Mechanism for HTTP Adaptive Streaming ASHKAN SOBHANI, ABDULSALAM YASSINE, and SHERVIN SHIRMOHAMMADI, University of Ottawa, Canada The Hypertext Transfer Protocol (HTTP) Adaptive Streaming (HAS) has now become ubiquitous and accounts for a large amount of video delivery over the Internet. But since the Internet is prone to bandwidth variations, HAS's up and down switching between different video bitrates to keep up with bandwidth variations leads to a reduction in Quality of Experience (QoE). In this article, we propose a video bitrate adaptation and prediction mechanism based on Fuzzy logic for HAS players, which takes into consideration the estimate of available network bandwidth as well as the predicted buffer occupancy level in order to proactively and intelligently respond to current conditions. This leads to two contributions: First, it allows HAS players to take appropriate actions, sooner than existing methods, to prevent playback interruptions caused by buffer underrun, reducing the ON-OFF traffic phenomena associated with current approaches and increasing the QoE. Second, it facilitates fair sharing of bandwidth among competing players at the bottleneck link. We present the implementation of our proposed mechanism and provide both empirical/QoE analysis and performance comparison with existing work. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) Association for Computing Machinery

A Video Bitrate Adaptation and Prediction Mechanism for HTTP Adaptive Streaming

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2017 by ACM Inc.
ISSN
1551-6857
DOI
10.1145/3052822
Publisher site
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Abstract

A Video Bitrate Adaptation and Prediction Mechanism for HTTP Adaptive Streaming ASHKAN SOBHANI, ABDULSALAM YASSINE, and SHERVIN SHIRMOHAMMADI, University of Ottawa, Canada The Hypertext Transfer Protocol (HTTP) Adaptive Streaming (HAS) has now become ubiquitous and accounts for a large amount of video delivery over the Internet. But since the Internet is prone to bandwidth variations, HAS's up and down switching between different video bitrates to keep up with bandwidth variations leads to a reduction in Quality of Experience (QoE). In this article, we propose a video bitrate adaptation and prediction mechanism based on Fuzzy logic for HAS players, which takes into consideration the estimate of available network bandwidth as well as the predicted buffer occupancy level in order to proactively and intelligently respond to current conditions. This leads to two contributions: First, it allows HAS players to take appropriate actions, sooner than existing methods, to prevent playback interruptions caused by buffer underrun, reducing the ON-OFF traffic phenomena associated with current approaches and increasing the QoE. Second, it facilitates fair sharing of bandwidth among competing players at the bottleneck link. We present the implementation of our proposed mechanism and provide both empirical/QoE analysis and performance comparison with existing work.

Journal

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) – Association for Computing Machinery

Published: Mar 27, 2017

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