Harnessing WebRTC for Large-Scale Live Streaming
Wei Zhang, Tong Meng, Xianhua Zeng, Wei Yang, Changqing Yan, Chao Li, Chenguang Li, Feng Qian, Junfeng Yang, Lei Zhang, Zhi Wang
摘要
Live streaming that supports real-time interaction has become increasingly popular. To support the ensuing requirements on low end-to-end latency, RTM, the state-of-the-art live streaming system at Douyin, replaces the HTTP-FLV streaming protocol with We-bRTC. To tailor the WebRTC stack to the live streaming scenario, we focus on optimizing first-frame delay, startup video rebuffering, audio-to-video drift, and per-session CPU usage. Those are the top-priority metrics identified from an importance analysis with respect to two user engagement metrics, i.e., viewer penetration and viewing time. To date, WebRTC-based streaming in RTM has been in operation for 4 years, and serves billions of viewer sessions every day. It dramatically optimizes QoE metrics (e.g., end-to-end latency reduced by 54.5%), and delivers statistically significant user engagement gains (e.g., number of paid orders increased by 0.8%). In this paper, we report our deployment experiences comprehensively.
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引用它的顶会 Paper2
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- RLive: Robust Delivery System for Scaling Live Streaming ServicesYu Tian, Gerui Lv, Qinghua Wu, Ruili Fang 等EuroSys 2026
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- Computers Can Learn from the Heuristic Designs and Master Internet Congestion ControlChen-Yu Yen, Soheil Abbasloo, H. Jonathan ChaoSIGCOMM 2023 · 被引用 73 次
- LiveNet: a low-latency video transport network for large-scale live streamingJinyang Li, Zhenyu Li, Ri Lu, Kai Xiao 等SIGCOMM 2022 · 被引用 59 次
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