Scalable BGP Simulation of Hyper-Scale Data Center Networks
Mengrui Zhang, X. Y. Zheng, Lizhao You, Ziyang Yao, Yang Wang, Rui Wen, Zhi Zhang, Ronghua Sun, Yuanhui Zhong, Haihua Li, Fei Yuan, Yuanxun Kang, Qiao Xiang · 2025
Modern cloud data center networks (DCNs) are hyper-scale, consisting of tens of thousands of switches, which poses significant challenges for simulation-based control-plane verification. Existing simulation tools face three key limitations when simulating BGP in such large-scale DCNs: poor scalability in large topologies, inaccuracy under non-monotonic configurations, and a lack of support for incremental simulation. To overcome these challenges, we present vBGPSim, a versatile BGP simulator designed for hyper-scale DCNs. vBGPSim enhances scalability through topology compression and a generalized Dijkstra's algorithm that replaces the iterative algorithm. It improves simulation accuracy under the non-monotonic configurations by integrating a withdrawal mechanism into Dijkstra's algorithm and supports incremental simulation using the same mechanism. Extensive evaluations on production and synthetic DCNs show that vBGPSim scales to networks with over 10,000 switches, while accurately handling non-monotonic updates and supporting efficient incremental simulation.