Fiel trial of Quality driven Video Streaming

Crabtree, Barry; Appleby, Steve; Nilsson, Mike; Ormston, Chris; Turnbull, R.S.; Park, Adastral

doi:10.1109/ccnc.2012.6180987

Cited by 1 publication

(2 citation statements)

References 2 publications

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“…We have identified several existing quality-based HAS schemes [13,9,10,7,8] (refer to Section 8 for discussions). However, they either focus on a different perspective (e.g., encoding, cross-stream optimization), or are based on different assumptions (e.g., scalable coded video source, statistically stationary source/channel models).…”

Section: Performance Evaluationmentioning

confidence: 99%

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Streaming video over HTTP with consistent quality

Begen

Gahm³

et al. 2014

Proceedings of the 5th ACM Multimedia Systems Conference

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In conventional HTTP-based adaptive streaming (HAS), a video source is encoded at multiple levels of constant bitrate representations, and a client makes its representation selections according to the measured network bandwidth. While greatly simplifying adaptation to the varying network conditions, this strategy is not the best for optimizing the video quality experienced by end users. Quality fluctuation can be reduced if the natural variability of video content is taken into consideration. In this work, we study the design of a client rate adaptation algorithm to yield consistent video quality. We assume that clients have visibility into incoming video within a finite horizon. We also take advantage of the client-side video buffer, by using it as a breathing room for not only network bandwidth variability, but also video bitrate variability. The challenge, however, lies in how to balance these two variabilities to yield consistent video quality without risking a buffer underrun. We propose an optimization solution that uses an online algorithm to adapt the video bitrate step-by-step, while applying dynamic programming at each step. We incorporate our solution into PANDA -a practical rate adaptation algorithm designed for HAS deployment at scale.

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Section: Performance Evaluationmentioning

confidence: 99%

“…Crabtree et al report the gains in terms of bitrate saved by using a quality-optimized approach to HAS [7]. Their technical discussion mainly focuses on how to assemble a constant quality video stream out of many CBR streams.…”

Section: Related Workmentioning

confidence: 99%

Streaming video over HTTP with consistent quality

Begen

Gahm³

et al. 2014

Proceedings of the 5th ACM Multimedia Systems Conference

View full text Add to dashboard Cite

show abstract

Fiel trial of Quality driven Video Streaming

Cited by 1 publication

References 2 publications

Streaming video over HTTP with consistent quality

Streaming video over HTTP with consistent quality

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