When BBR Meets Live Streaming
2026-06-02 • Multimedia
MultimediaNetworking and Internet Architecture
AI summaryⓘ
The authors looked at BBR, a tool used to control internet traffic, and found that it doesn’t work well for live-streaming because it guesses bandwidth poorly. This causes problems like staying stuck in a startup phase and sending less data than possible. To fix this, they created BBR-Copilot, which helps BBR by smartly measuring bandwidth more accurately using extra data. Their tests showed that BBR-Copilot improves BBR’s performance for live streaming. This means live videos can be sent more smoothly over the internet.
BBRcongestion controlbandwidth estimationlive streamingQUIC protocolstartup phaseself-inflicted lossbandwidth measurement
Authors
Xu Yan, Tong Li, Bo Wu, Cheng Luo, Jiuxiang Zhu, Laizhong Cui
Abstract
Recently, industrial pioneers like Amazon, Tencent, ByteDance, and Huawei have been adopting BBR as their congestion control algorithm for live-streaming applications, including TikTok Live. However, BBR, originally crafted for bulk data transmission, faces multiple challenges in live-streaming scenarios. In this paper, we first explore two key issues associated with BBR due to inaccurate bandwidth estimation in live-streaming scenarios: (i) BBR cannot easily exit its startup phase, resulting in a fierce self-inflicted loss. (ii) BBR sends data at a lower rate than the available bandwidth during its stable phase. We then propose BBR-Copilot, an auxiliary congestion control component that cooperates with BBR, making BBR better adapt to live-streaming scenarios. BBR-Copilot allows for proactively generating accurate bandwidth measurement samples by smartly creating and sending extra data. We implement the BBR-Copilot prototype upon QUIC and evaluate it via testbed. Experimental evaluation results show that BBR-Copilot effectively enhances BBR's performance in live-streaming scenarios.