Thursday, April 4, 2019

ACM NOSSDAV'19: Bandwidth Prediction in Low-Latency Chunked Streaming

Bandwidth Prediction in Low-Latency Chunked Streaming

[PDF]

Abdelhak Bentaleb (National University of Singapore), Christian Timmerer (Alpen-Adria Universität & Bitmovin Inc,), Ali C. Begen (Ozyegin University), and Roger Zimmermann (National University of Singapore)

Abstract: HTTP adaptive streaming (HAS) with chunked transfer encoding can be used to reduce latency without sacrificing the coding ef- ficiency. While this allows a media segment to be generated and delivered at the same time, it also causes grossly inaccurate band- width measurements, leading to incorrect bitrate selections. To overcome this effect, we design a novel Adaptive bitrate scheme for Chunked Transfer Encoding (ACTE) that leverages the unique nature of chunk downloads. It uses a sliding window to accurately measure the available bandwidth and an online linear adaptive filter to predict the available bandwidth into the future. Results show that ACTE achieves 96% measurement accuracy, which translates to a 64% reduction in stalls and a 27% increase in video quality.


Keywords: HAS; ABR; DASH; CMAF; low-latency; HTTP chunked transfer encoding; bandwidth measurement and prediction; RLS.

Acknowledgment: This research has been supported in part by the Singapore Ministry of Education Academic Research Fund Tier 1 under MOE's official grant number T1 251RES1820 and the Austrian Research Promotion Agency (FFG) under the Next Generation Video Streaming project "PROMETHEUS".

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