Bitrate adaptation in backward-shifted coding for HTTP adaptive video streaming
| Autor: | Stefan Valentin, Zakaria Ye, Rachid El-Azouzi, Tania Jimenez, Francesco De Pellegrini |
|---|---|
| Přispěvatelé: | Jimenez, Tania |
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Computer science [INFO.INFO-SI] Computer Science [cs]/Social and Information Networks [cs.SI] Quality of service Real-time computing Constant bitrate 020206 networking & telecommunications 02 engineering and technology [INFO] Computer Science [cs] Video quality Variable bitrate Scalable Video Coding Bit rate 0202 electrical engineering electronic engineering information engineering Fading [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation business ComputingMilieux_MISCELLANEOUS Coding (social sciences) Computer network |
| Zdroj: | ICC |
| DOI: | 10.1109/icc.2017.7996744 |
| Popis: | HTTP Adaptive Streaming is able to dynamically match video quality to variable network conditions. This is a key feature for multimedia delivery when quality of service cannot be granted network-wide. For instance, the end-to-end throughput towards mobile terminals may suffer short term fluctuations due to fading. Hence, robust bitrate adaptation schemes become crucial in order to avoid degraded video reproduction. The objective, in this context, is to control the filling level of the playback buffer, maximize the video quality, and avoid unnecessary quality variations which may also impair the perceived quality of experience. In this work we study bitrate adaptation algorithms leveraging on Backward-Shifted Coding (BSC), a scalable video coding scheme able to cope with the effects of end-to-end throughput fluctuations. We have proposed a new adaptation scheme able to balance video rate smoothness and high network capacity utilization. Both the throughput-based and buffer-based variants of such scheme have been designed. Extensive simulations using synthetic and real-world video traffic traces show that the proposed solution performs remarkably well even under challenging network conditions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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