Re-Architecting Traffic Control in Cross-Datacenter RDMA Networks
The network-intensive applications, like machine learning and cloud storage, are increasingly driving two critical trends: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1)</i> RDMA has been widely deployed to provide high-speed networks; <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2)</i> applications are distributively deployed across multiple regional datacenters to satisfy demands for content providers and customers. To fully utilize the benefits of RDMA, we desire to extend it to support cross-datacenter networks. However, the long-haul transport suffers a considerably long control loop, and thus the hybrid of long-haul and intra-datacenter traffic can easily cause severe congestion. We revisit existing traffic control methods and find they are insufficient to resolve this hybrid traffic congestion. Generally, regional datacenters are connected using dedicated long-haul optical fiber and datacenter interconnection (DCI) switches. In this paper, we propose Approach Traffic Control (ATC), a novel solution focusing on two-side DCI-switches (i.e., the approach point for datacenters) to separately alleviate the hybrid traffic congestion in the local and distal datacenters, as a building block for host-driven control methods. This design principle helps ATC shorten the control loop to a single datacenter scale while aggregating congestion information of the whole datacenter range with minor deployment complexity. We implement ATC on P4-based switches and conduct evaluations using real-world testbeds and large-scale NS3 simulations. The results show that ATC ensures fast congestion avoidance and delivers significant performance. For example, ATC reduces the FCT of intra-datacenter and long-haul traffic by up to 88% and 52%, respectively.
Authors
- Zirui Wan (ORCID: https://orcid.org/0009-0000-1673-8104)
- Mingxuan Yu (ORCID: https://orcid.org/0009-0004-5056-0361)
- Tao Huang (ORCID: https://orcid.org/0000-0002-3545-1122)
- Haoyu Pan (ORCID: https://orcid.org/0009-0008-0212-3780)
- Jiao Zhang (ORCID: https://orcid.org/0000-0001-5614-3420)
- Yuzhen Su (ORCID: https://orcid.org/0009-0007-2070-8216)
- Yuan Li (ORCID: https://orcid.org/0009-0004-2797-0397)
Institutions
- Beijing University of Posts and Telecommunications (CN)
Publication Details
- Journal
- IEEE Transactions on Networking
- Published
- 2025-05-22
- DOI
- https://doi.org/10.1109/ton.2025.3569630
- Citations
- 4
- Primary Topic
- Software-Defined Networks and 5G
- Type
- article
- Field-Weighted Citation Impact
- 5.95
Funders
- National Natural Science Foundation of China
- Beijing University of Posts and Telecommunications
- Natural Science Foundation of Shandong Province
- National Key Research and Development Program of China