Precise Data Center Traffic Engineering with Constrained Hardware Resources
Shawn Shuoshuo Chen, Keqiang He, Rui Wang, Srinivasan Seshan, Peter Steenkiste
Abstract
Data center traffic engineering (TE) routes flows over a set of available paths following custom weight distributions to achieve optimal load balancing or flow throughput. However, as a result of hardware constraints, it is challenging, and often impossible for larger data center networks, to precisely implement the TE weight distributions on the data plane switches. The resulting precision loss in the TE implementation causes load imbalances that can result in congestion and traffic loss.
Instead of treating all flows equally, we adapt the hardware resource allocation to a flow's traffic volume and its contribution to the overall precision loss. We intelligently prune select ports in weight distributions and merge identical distributions to free up hardware resources. Evaluation using realistic traffic loads shows that our techniques approximate ideal TE solutions under various scenarios within 7% error, compared to a 67% error for today's state-of-the-art approach. In addition, our design avoids traffic loss triggered by switch rule overflow. Finally, the execution time is 10× faster than the current approach.
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 e9ed2d36-3212-4b19-915e-ca51364d1362Cited by top-tier papers2
- MegaTE: Extending WAN Traffic Engineering to Millions of Endpoints in Virtualized CloudCongcong Miao, Zhizhen Zhong, Yunming Xiao, Feng Yang et al.SIGCOMM 2024 · 14 citations
- LCMP: Distributed Long-Haul Cost-Aware Multi-Path Routing for Inter-Datacenter RDMA NetworksDong-Yang Yu, Yuchao Zhang, Xiaodi Wang, Jun Wang et al.EuroSys 2026 · 2 citations
Builds on18
- Jupiter evolving: transforming google's datacenter network via optical circuit switches and software-defined networkingLeon Poutievski, Omid Mashayekhi, Joon Ong, Arjun Singh et al.SIGCOMM 2022 · 230 citations
- When Cloud Storage Meets RDMAYixiao Gao, Qiang Li, Lingbo Tang, Yongqing Xi et al.NSDI 2021 · 228 citations
- TopoOpt: Co-optimizing Network Topology and Parallelization Strategy for Distributed Training JobsWeiyang Wang, Moein Khazraee, Zhizhen Zhong, Manya Ghobadi et al.NSDI 2023 · 215 citations
- Sirius: A Flat Datacenter Network with Nanosecond Optical SwitchingHitesh Ballani, Paolo Costa, Raphael Behrendt, Daniel Cletheroe et al.SIGCOMM 2020 · 204 citations
- Expanding across time to deliver bandwidth efficiency and low latencyWilliam M. Mellette, Rajdeep Das, Yibo Guo, Rob McGuinness et al.NSDI 2020 · 194 citations
Related papers
- FIGRET: Fine-Grained Robustness-Enhanced Traffic EngineeringXimeng Liu, Shizhen Zhao, Yong Cui, Xinbing WangSIGCOMM 2024 · 36 citations
- Contracting Wide-area Network Topologies to Solve Flow Problems QuicklyFiras Abuzaid, Srikanth Kandula, Behnaz Arzani, Ishai Menache et al.NSDI 2021 · 101 citations
- A Fast Solver-Free Algorithm for Traffic Engineering in Large-Scale Data Center NetworkYingming Mao, Qiaozhu Zhai, Ximeng Liu, Zhen Yao et al.NSDI 2026 · 2 citations
- Unlocking ECMP Programmability for Precise Traffic ControlYadong Liu, Yunming Xiao, Xuan Zhang, Weizhen Dang et al.NSDI 2025 · 10 citations
- Online Joint Optimization on Traffic Engineering and Network Update in Software-defined WANsJiaqi Zheng, Yimeng Xu, Li Wang, Haipeng Dai et al.INFOCOM 2021 · 9 citations
