Weitao Wang, Google LLC and Rice University; Masoud Moshref, Yuliang Li, and Gautam Kumar, Google LLC; T. S. Eugene Ng, Rice University; Neal Cardwell and Nandita Dukkipati, Google LLC
The difficulty in gaining visibility into the fine-timescale hop-level congestion state of networks has been a key challenge faced by congestion control (CC) protocols for decades. However, the emergence of commodity switches supporting in-network telemetry (INT) enables more advanced CC. In this paper, we present Poseidon, a novel CC protocol that exploits INT to address blind spots of CC algorithms and realize several fundamentally advantageous properties. First, Poseidon is efficient: it achieves low queuing delay, high throughput, and fast convergence. Furthermore, Poseidon decouples bandwidth fairness from the traditional AIMD control law, using a novel adaptive update scheme that converges quickly and smooths out oscillations. Second, Poseidon is robust: it realizes CC for the actual bottleneck hop, and achieves maxmin fairness across traffic patterns, including multi-hop and reverse-path congestion. Third, Poseidon is practical: it is amenable to incremental brownfield deployment in networks that mix INT and non-INT switches. We show, via testbed and simulation experiments, that Poseidon provides significant improvements over the state-of-the-art Swift CC algorithm across key metrics – RTT, throughput, fairness, and convergence – resulting in end-to-end application performance gains. Evaluated across several scenarios, Poseidon lowers fabric RTT by up to 50%, reduces time to converge up to 12×, and decreases throughput variation across flows by up to 70%. Collectively, these improvements reduce message transfer time by more than 61% on average and 14.5× at 99.9p.
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author = {Weitao Wang and Masoud Moshref and Yuliang Li and Gautam Kumar and T. S. Eugene Ng and Neal Cardwell and Nandita Dukkipati},
title = {Poseidon: Efficient, Robust, and Practical Datacenter {CC} via Deployable {INT}},
booktitle = {20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23)},
year = {2023},
isbn = {978-1-939133-33-5},
address = {Boston, MA},
pages = {255--274},
url = {https://www.usenix.org/conference/nsdi23/presentation/wang-weitao},
publisher = {USENIX Association},
month = apr
}