labmeeting - 20151013 - adaptive video streaming over http with dynamic resource estimation

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NTUST - Mobilizing Information Technology Lab Adaptive Video Streaming over HTTP with Dynamic Resource Estimation Truong Cong Thang Univ. of Aizu, Aizu-Wakamatsu, Japan Le, H.T. ; Nguyen, H.X. ; Pham, A.T. ; Jung Won Kang ; Yong Man Ro Journal of Communications and Networks, Vol. 15, No. 6, Dec. 2013 Advisor Jenq-Shiou Leu Student Bing-Syuan Wang Date 2015/10/13 National Taiwan University of Science and Technology

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Page 1: Labmeeting - 20151013 - Adaptive Video Streaming over HTTP with Dynamic Resource Estimation

NTUST - Mobilizing Information Technology Lab

Adaptive Video Streaming over HTTP with Dynamic Resource Estimation

Truong Cong Thang Univ. of Aizu, Aizu-Wakamatsu, JapanLe, H.T. ; Nguyen, H.X. ; Pham, A.T. ; Jung Won Kang ; Yong Man RoJournal of Communications and Networks, Vol. 15, No. 6, Dec. 2013

Advisor: Jenq-Shiou LeuStudent: Bing-Syuan WangDate: 2015/10/13National Taiwan University of Science and Technology

Page 2: Labmeeting - 20151013 - Adaptive Video Streaming over HTTP with Dynamic Resource Estimation

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Outline• Introduction• Overview of Adaptive HTTP Streaming• Throughput Estimation• Experiments• Video Bitrate Estimation• Experiments• Conclusion

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Introduction• Hypertext transfer protocol (HTTP) streaming has become a cost effective

means for multimedia delivery.

• Client-based approach.

• Bandwidth estimation. Bitrate estimation.

• Constant bitrate (CBR) video/Variable bitrate (VBR) video.• This solution may enable CBR-streaming even though the video is encoded in

VBR mode

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Overview of Adaptive HTTP Streaming• Dynamic adaptive streaming over HTTP (DASH)• Metadata: media presentation description (MPD)

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Throughput Estimation• Based on previous segment throughputs / last segment (aggressive method).

Page 6: Labmeeting - 20151013 - Adaptive Video Streaming over HTTP with Dynamic Resource Estimation

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Throughput Estimation• : The estimated download throughput• : The estimated download duration

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Experiments• Segment duration 6s; target buffer level 12s.• Client behavior with segment duration of 6 s and throughput estimation using:

(a) Aggressive method and (b) proposed method.

11.5s6s

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Experiments• Comparison of the aggressive method and proposed method with segment

duration of 6 s using: (a) CDF of bitrate and (b) CDF of buffer level.

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Video Bitrate Estimation• The bitrate is not constant.• The client will be able to dynamically select the highest possible bitrate.• Quantization parameter (QP)

(1-unit QP → 12%)

• A. Inter-Stream Bitrate Estimation

• B. Intra-Stream Bitrate Estimation

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Experiments• Segment duration 2s; target buffer level 4s.• Preparing the video alternatives in VBR mode.

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Experiments• Based on average bitrate (ABR), highest bitrate (HBR), estimated bitrate

(EBR)

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Conclusion• The proposed method can capture quickly the changes of throughput, and

then adjust video bitrate accordingly.

• The estimation methods essentially do not affect the playback quality (less than 1 ms).

• The proposed solutions were effective to maintain a stable buffer under fluctuations of bandwidth and video bitrate.