@inproceedings{goyal2022backpressure,
author = {Goyal, Prateesh and Shah, Preey and Zhao, Kevin and Nikolaidis, Georgios and Alizadeh, Mohammad and Anderson, Thomas E.},
title = {Backpressure Flow Control},
booktitle = {USENIX NSDI},
year = {2022},
month = {April},
abstract = {Effective congestion control for data center networks is becoming increasingly challenging with a growing amount of latency-sensitive traffic, much fatter links, and extremely bursty traffic. Widely deployed algorithms, such as DCTCP and DCQCN, are still far from optimal in many plausible scenarios, particularly for tail latency. Many operators compensate by running their networks at low average utilization, dramatically increasing costs.

In this paper, we argue that we have reached the practical limits of end-to-end congestion control. Instead, we propose, implement, and evaluate a new congestion control architecture called Backpressure Flow Control (BFC). BFC provides per-hop per-flow flow control, but with bounded state, constant-time switch operations, and careful use of buffers and queues. We demonstrate BFC’s feasibility by implementing it on Tofino2, a state-of-the-art P4-based programmable hardware switch. In simulation, we show that BFC achieves near optimal throughput and tail latency behavior even under challenging conditions such as high network load and incast cross traffic. Compared to deployed end-to-end schemes, BFC achieves 2.3 - 60× lower tail latency for short flows and 1.6 - 5× better average completion time for long flows.},
url = {http://approjects.co.za/?big=en-us/research/publication/backpressure-flow-control/},
}