Poseidon: Efficient, Robust, and Practical Datacenter CC via Deployable INT
Weitao Wang, Masoud Moshref, Yuliang Li, Gautam Kumar, T. S. Eugene Ng, Neal Cardwell, Nandita Dukkipati
Abstract
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.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 6efe62db-8389-421b-9aae-3b188c13d153Cited by top-tier papers15
- Empowering Azure Storage with RDMAWei Bai, Shanim Sainul Abdeen, Ankit Agrawal, Krishan Kumar Attre et al.NSDI 2023 · 117 citations
- Crux: GPU-Efficient Communication Scheduling for Deep Learning TrainingJiamin Cao, Yu Guan, Kun Qian, Jiaqi Gao et al.SIGCOMM 2024 · 60 citations
- Solving Max-Min Fair Resource Allocations Quickly on Large GraphsPooria Namyar, Behnaz Arzani, Srikanth Kandula, Santiago Segarra et al.NSDI 2024 · 29 citations
- Pyrrha: Congestion-Root-Based Flow Control to Eliminate Head-of-Line Blocking in DatacenterKexin Liu, Zhaochen Zhang, Chang Liu, Yizhi Wang et al.NSDI 2025 · 13 citations
- Enabling Virtual Priority in Data Center Congestion ControlZhaochen Zhang, Feiyang Xue, Keqiang He, Zhimeng Yin et al.EuroSys 2025 · 6 citations
Builds on10
- ATP: In-network Aggregation for Multi-tenant LearningChonLam Lao, Yanfang Le, Kshiteej Mahajan, Yixi Chen et al.NSDI 2021 · 359 citations
- Swift: Delay is Simple and Effective for Congestion Control in the DatacenterGautam Kumar, Nandita Dukkipati, Keon Jang, Hassan M. G. Wassel et al.SIGCOMM 2020 · 333 citations
- PINT: Probabilistic In-band Network TelemetryRan Ben Basat, Sivaramakrishnan Ramanathan, Yuliang Li, Gianni Antichi et al.SIGCOMM 2020 · 268 citations
- Can far memory improve job throughput?Emmanuel Amaro, Christopher Branner-Augmon, Zhihong Luo, Amy Ousterhout et al.EuroSys 2020 · 163 citations
- PowerTCP: Pushing the Performance Limits of Datacenter NetworksVamsi Addanki, Oliver Michel, Stefan SchmidNSDI 2022 · 116 citations
Related papers
- OSCAR: O(1)-Step Convergence and Readily-deployable Congestion ControlZhaochen Zhang, Feiyang Xue, Rui Ning, Keqiang He et al.NSDI 2026
- CSIG: Congestion Signaling for Datacenter TransportsAbhiram Ravi, Nandita Dukkipati, Weiwu Pang, Neal Cardwell et al.SIGCOMM 2026
- CCC: Re-architecting Delay-based Congestion Control in Datacenter NetworksWanchun Jiang, Haoyang Li, Kai Wang, Yujie Hu et al.NSDI 2026 · 1 citation
- BCC: Re-architecting Congestion Control in DCNsQingkai Meng, Shan Zhang, Zhiyuan Wang, Tao Tong et al.INFOCOM 2024 · 11 citations
- INT-label: Lightweight In-band Network-Wide Telemetry via Interval-based Distributed LabellingEnge Song, Tian Pan, Chenhao Jia, Wendi Cao et al.INFOCOM 2021 · 40 citations
