论文标题
SQP：低延迟交互式视频流的拥塞控制
SQP: Congestion Control for Low-Latency Interactive Video Streaming
论文作者
论文摘要
本文介绍了SQP的设计和评估，SQP是一种交互式视频流算应用程序的拥堵控制算法（CCA），需要以非常低的端到端框架延迟（例如AR流媒体，云游戏）流式传输高倍率压缩视频。 SQP使用框架耦合，节奏的数据包列来采样网络带宽，并使用自适应的单向延迟测量测量来从排队，低，有限的排队延迟中恢复。 SQP迅速适应了链路带宽的变化，确保高利用率和较小的帧延迟，并在与可接受的延迟信封内与队列建造流竞争时也可以实现竞争性带宽份额。 SQP具有良好的公平性能，并且可以很好地与浅缓冲区的链接效果。 在Google AR流媒体平台对COPA的现实世界A/B测试中，SQP分别在LTE和Wi-Fi的较高比特率和较低的帧延迟中获得了27％和15％的会话。与Cutic和BBR等队列建设流量竞争时，与Googcc（WEBRTC），Sprout和PCC-Vivace相比，SQP的带宽高2-3x，与COPA（具有模式切换）相当的性能。
This paper presents the design and evaluation of SQP, a congestion control algorithm (CCA) for interactive video streaming applications that need to stream high-bitrate compressed video with very low end-to-end frame delay (eg. AR streaming, cloud gaming). SQP uses frame-coupled, paced packet trains to sample the network bandwidth, and uses an adaptive one-way delay measurement to recover from queuing, for low, bounded queuing delay. SQP rapidly adapts to changes in the link bandwidth, ensuring high utilization and low frame delay, and also achieves competitive bandwidth shares when competing with queue-building flows within an acceptable delay envelope. SQP has good fairness properties, and works well on links with shallow buffers. In real-world A/B testing of SQP against Copa in Google's AR streaming platform, SQP achieves 27% and 15% more sessions with high bitrate and low frame delay for LTE and Wi-Fi, respectively. When competing with queue-building traffic like Cubic and BBR, SQP achieves 2-3X higher bandwidth compared to GoogCC (WebRTC), Sprout, and PCC-Vivace, and comparable performance to Copa (with mode switching).
