SFC: Near-Source Congestion Signaling and Flow Control
Yanfang Le, Jeongkeun Lee, Jeremias Blendin, Jiayi Chen, Nikolaidis, Georgios, Rong Pan, Robert Soulé, Aditya Akella, Segura, Pedro Yebenes, Arjun Singhvi, Yuliang Li, Qingkai Meng, Changhoon Kim, Serhat Arslan · arXiv (Cornell University) · 2023
State-of-the-art congestion control algorithms for data centers alone do not cope well with transient congestion and high traffic bursts. To help with these, we revisit the concept of direct \emph{backward} feedback from switches and propose Back-to-Sender (BTS) signaling to many concurrent incast senders. Combining it with our novel approach to in-network caching, we achieve near-source sub-RTT congestion signaling. Source Flow Control (SFC) combines these two simple signaling mechanisms to instantly pause traffic sources, hence avoiding the head-of-line blocking problem of conventional hop-by-hop flow control. Our prototype system and scale simulations demonstrate that near-source signaling can significantly reduce the message completion time of various workloads in the presence of incast, complementing existing congestion control algorithms. Our results show that SFC can reduce the $99^{th}$-percentile flow completion times by $1.2-6\times$ and the peak switch buffer usage by $2-3\times$ compared to the recent incast solutions.