Enabling Virtual Priority in Data Center Congestion Control
Zhaochen Zhang, Feiyang Xue, Keqiang He, Zhimeng Yin, Gianni Antichi, Jiaqi Gao, Yizhi Wang, Rui Ning, Haixin Nan, Xu Zhang, Peirui Cao, Xiaoliang Wang
Abstract
In data center networks, various types of traffic with strict performance requirements operate simultaneously, necessitating effective isolation and scheduling through priority queues. However, most switches support only around ten priority queues. Virtual priority can address this limitation by emulating multi-priority queues on a single physical queue, but existing solutions often require complex switch-level scheduling and hardware changes. Our key insight is that virtual priority can be achieved by carefully managing bandwidth contention in a physical queue, which is traditionally handled by congestion control (CC) algorithms. Hence, the virtual priority mechanism needs to be tightly coupled with CC. In this paper, we propose PrioPlus, a CC enhancement algorithm that can be integrated with existing congestion control schemes to enable virtual priority transmission. PrioPlus assigns specific delay ranges to different priority levels, ensuring that flows transmit only when the delay is within the assigned range, effectively meeting virtual priority requirements. Compared to Swift CC with physical priority queues, PrioPlus provides strict priority for high-priority flows without impacting performance sensibly. Meanwhile, it benefits low-priority flows from 25% to 41% as its priority-aware design enhances CC's ability to fully utilize available bandwidth once higher-priority traffic completes. As a result, in coflow and model training scenarios, PrioPlus improves job completion times by 21% and 33%, respectively, compared to Swift with physical priority queues.
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.
Cited by top-tier papers1
Ask how each one uses itBuilds on20
- 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
- When Cloud Storage Meets RDMAYixiao Gao, Qiang Li, Lingbo Tang, Yongqing Xi et al.NSDI 2021 · 228 citations
- RDMA over Ethernet for Distributed Training at Meta ScaleAdithya Gangidi, Rui Miao, Shengbao Zheng, Sai Jayesh Bondu et al.SIGCOMM 2024 · 171 citations
- CASSINI: Network-Aware Job Scheduling in Machine Learning ClustersSudarsanan Rajasekaran, Manya Ghobadi, Aditya AkellaNSDI 2024 · 144 citations
- Empowering Azure Storage with RDMAWei Bai, Shanim Sainul Abdeen, Ankit Agrawal, Krishan Kumar Attre et al.NSDI 2023 · 117 citations
Related papers
- Augmented Queue: A Scalable In-Network Abstraction for Data Center Network SharingXinyu Crystal Wu, Zhuang Wang, Weitao Wang, T. S. Eugene NgSIGCOMM 2023 · 10 citations
- Simplifying Prioritization and Scheduling with P2CSAli Munir, Xiaolin Pang, Junyi ZhangSIGCOMM 2026
- Credence: Augmenting Datacenter Switch Buffer Sharing with ML PredictionsVamsi Addanki, Maciej Pacut, Stefan SchmidNSDI 2024 · 22 citations
- Bolt: Sub-RTT Congestion Control for Ultra-Low LatencySerhat Arslan, Yuliang Li, Gautam Kumar, Nandita DukkipatiNSDI 2023
- BBQ: A Fast and Scalable Integer Priority Queue for Hardware Packet SchedulingNirav Atre, Hugo Sadok, Justine SherryNSDI 2024 · 12 citations
