ATRO: A Fast Algorithm for Topology Engineering of Reconfigurable Datacenter Networks
Yingming Mao, Qiaozhu Zhai, Ximeng Liu, Xinchi Han, Fanfan Li, Shizhen Zhao, Yuzhou Zhou, Zhen Yao, Xia Zhu
Abstract
Reconfigurable data center networks (DCNs) enhance traditional architectures with optical circuit switches (OCSs), enabling dynamic reconfiguration of inter-PoD links, i.e., the logical topology. Optimizing this topology is crucial for adapting to traffic dynamics but is challenging due to its combinatorial nature. The complexity increases further when demands can be distributed across multiple paths, requiring joint optimization of topology and routing. We propose Alternating Topology and Routing Optimization (ATRO), a unified framework that supports both one-hop topology optimization (where traffic is routed via direct paths) and multi-hop joint optimization (where routing is also optimized). Although these settings differ in constraints, both are combinatorially hard and challenge solver-based methods. ATRO addresses both cases efficiently: in the one-hop case, it guarantees the global optimum via an accelerated binary search; in the multi-hop case, it alternates between topology and routing updates, with routing steps optionally accelerated by existing traffic engineering (TE) methods. ATRO supports warm-starting and improves solution quality monotonically across iterations. ATRO remains competitive even when paired with solver-free TE methods, forming a fully solver-free optimization pipeline that still outperforms prior approaches in runtime and maximum link utilization across diverse workloads.
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 e95e9542-7d59-4afe-bd8c-08d68f595d8bCited by top-tier papers1
Ask how each one uses itBuilds on11
- Orca: A Distributed Serving System for Transformer-Based Generative ModelsGyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, Soojeong Kim et al.OSDI 2022 · 690 citations
- 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
- Alibaba HPN: A Data Center Network for Large Language Model TrainingKun Qian, Yongqing Xi, Jiamin Cao, Jiaqi Gao et al.SIGCOMM 2024 · 173 citations
- Teal: Learning-Accelerated Optimization of WAN Traffic EngineeringZhiying Xu, Francis Y. Yan, Rachee Singh, Justin T. Chiu et al.SIGCOMM 2023 · 95 citations
- DOTE: Rethinking (Predictive) WAN Traffic EngineeringYarin Perry, Felipe Vieira Frujeri, Chaim Hoch, Srikanth Kandula et al.NSDI 2023 · 81 citations
Related papers
- 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
- 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
- Rearchitecting Datacenter Networks: A New Paradigm with Optical Core and Optical EdgeSushovan Das, Arlei Silva, T. S. Eugene NgINFOCOM 2024 · 5 citations
- Approximation Algorithms for Minimizing Congestion in Demand-Aware NetworksWenkai Dai, Michael Dinitz, Klaus-Tycho Foerster, Long Luo et al.INFOCOM 2024 · 4 citations
- NegotiaToR: Towards A Simple Yet Effective On-demand Reconfigurable Datacenter NetworkCong Liang, Xiangli Song, Jing Cheng, Mowei Wang et al.SIGCOMM 2024 · 27 citations
