为BBR设计协作组件，提升直播流传输性能
When BBR Meets Live Streaming
- 用额外数据主动生成精准带宽样本，辅助BBR判断
- 实测在直播场景中显著减少丢包，提升传输速率
- 适合需要低延迟直播的系统开发者参考
近年来，亚马逊、腾讯、字节跳动和华为等企业已将BBR用于直播应用（如TikTok Live）。然而，原为批量数据传输设计的BBR在直播场景中面临带宽估计不准的问题：一是难以退出启动阶段，导致自毁式丢包；二是稳定阶段发送速率低于可用带宽。本文提出BBR-Copilot，一种与BBR协同的辅助拥塞控制模块，通过智能生成并发送额外数据，主动获取准确带宽测量样本。我们在QUIC协议上实现原型，并通过测试床评估。实验结果表明，BBR-Copilot能有效提升BBR在直播场景下的性能。
原文摘要 · Abstract (English)
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.
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