research-article

Neural-Enhanced Live Streaming: Improving Live Video Ingest via Online Learning

Authors:

Dongsu HanAuthors Info & Claims

SIGCOMM '20: Proceedings of the Annual conference of the ACM Special Interest Group on Data Communication on the applications, technologies, architectures, and protocols for computer communication

Pages 107 - 125

https://doi.org/10.1145/3387514.3405856

Published: 30 July 2020 Publication History

Abstract

Live video accounts for a significant volume of today's Internet video. Despite a large number of efforts to enhance user quality of experience (QoE) both at the ingest and distribution side of live video, the fundamental limitations are that streamer's upstream bandwidth and computational capacity limit the quality of experience of thousands of viewers.

To overcome this limitation, we design LiveNAS, a new live video ingest framework that enhances the origin stream's quality by leveraging computation at ingest servers. Our ingest server applies neural super-resolution on the original stream, while imposing minimal overhead on ingest clients. LiveNAS employs online learning to maximize the quality gain and dynamically adjusts the resource use to the real-time quality improvement. LiveNAS delivers high-quality live streams up to 4K resolution, outperforming WebRTC by 1.96 dB on average in Peak-Signal-to-Noise-Ratio on real video streams and network traces, which leads to 12%-69% QoE improvement for live stream viewers.

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20-minute talk about Neural-Enhanced Live Streaming: Improving Live Video Ingest via Online Learning presented at SIGCOMM' 20

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Cited By

Wang LSingh SChakareski JHajiesmaili MSitaraman R(2024)BONES: Near-Optimal Neural-Enhanced Video StreamingProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/36560148:2(1-28)Online publication date: 29-May-2024
https://dl.acm.org/doi/10.1145/3656014
Chen BWu MGuo HYan ZNahrstedt K(2024)VesperProceedings of the 15th ACM Multimedia Systems Conference10.1145/3625468.3647621(166-177)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1145/3625468.3647621
Jin SZhu RHassan AZhu XZhang XMao ZQian FZhang Z(2024)OASISProceedings of the 15th ACM Multimedia Systems Conference10.1145/3625468.3647610(45-55)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1145/3625468.3647610
Show More Cited By

Index Terms

Neural-Enhanced Live Streaming: Improving Live Video Ingest via Online Learning
1. Information systems
  1. Information systems applications
    1. Multimedia information systems
      1. Multimedia streaming
2. Networks
  1. Network algorithms
    1. Control path algorithms
      1. Network resources allocation

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cover image ACM Conferences

SIGCOMM '20: Proceedings of the Annual conference of the ACM Special Interest Group on Data Communication on the applications, technologies, architectures, and protocols for computer communication

July 2020

814 pages

ISBN:9781450379557

DOI:10.1145/3387514

Copyright © 2020 ACM.

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August 10 - 14, 2020

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Wang LSingh SChakareski JHajiesmaili MSitaraman R(2024)BONES: Near-Optimal Neural-Enhanced Video StreamingProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/36560148:2(1-28)Online publication date: 29-May-2024
https://dl.acm.org/doi/10.1145/3656014
Chen BWu MGuo HYan ZNahrstedt K(2024)VesperProceedings of the 15th ACM Multimedia Systems Conference10.1145/3625468.3647621(166-177)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1145/3625468.3647621
Jin SZhu RHassan AZhu XZhang XMao ZQian FZhang Z(2024)OASISProceedings of the 15th ACM Multimedia Systems Conference10.1145/3625468.3647610(45-55)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1145/3625468.3647610
Jeong SKim BCha SSeo KChang HLee JKim YNoh J(2024)Real-Time CNN Training and Compression for Neural-Enhanced Adaptive Live StreamingIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2024.337737246:9(6023-6039)Online publication date: Sep-2024
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