AnyTuner: Optimizing IP Anycast Performance via Strategic BGP Routing Policy
Optimizing anycast catchment to ensure clients connect to their expected PoPs remains a significant challenge in production networks, primarily due to BGP’s inherent lack of performance awareness. Existing approaches either lack fine-grained routing policy control or prove operationally impractical. In this paper, we present AnyTuner, an automatic route management system that strategically optimizes anycast performance through AS-path prepending and BGP communities. AnyTuner integrates three key components: a measurement-driven optimization loop, a neural network for PoP traffic matrix prediction, and an automated recommendation engine for configuration generation. Deployed for over two years on a commercial cloud platform, AnyTuner demonstrates remarkable efficacy in our evaluation across 18 PoPs and 9,000+ probes, achieving a 39.9% reduction in median RTT (from 36.3 ms to 21.8 ms) compared to policy-free baseline configurations and outperforming state-of-the-art alternatives like AnyOpt by 27.8%.
Authors
- Congying Wang (ORCID: https://orcid.org/0000-0002-7121-9961)
- Wanchun Dou (ORCID: https://orcid.org/0000-0003-4833-2023)
- M. B. Zhou (ORCID: https://orcid.org/0009-0007-3453-0033)
- Guihai Chen (ORCID: https://orcid.org/0000-0002-6934-1685)
- Jiaqi Zheng (ORCID: https://orcid.org/0000-0001-8403-9655)
Institutions
- Nanjing University (CN)
Publication Details
- Published
- 2025-09-22
- DOI
- https://doi.org/10.1109/icnp65844.2025.11192428
- Citations
- 1
- Primary Topic
- Network Traffic and Congestion Control
- Type
- article
- Field-Weighted Citation Impact
- 1.49