AnyPro: Preference-Preserving Anycast Optimization based on Strategic AS-Path Prepending

TL;DR

AnyPro is a system that optimizes large-scale anycast networks by strategically using AS-path prepending to improve client-to-site routing, significantly reducing latency.

Contribution

It introduces a novel, constraint-based approach to derive globally optimal ASPP configurations for performance-aware anycast routing at scale.

Findings

Reduces 90th percentile latency by 37.7% in tests.

Effectively identifies clients sensitive to ASPP changes.

Enhances performance when integrated with PoP-level optimization.

Abstract

Operating large-scale anycast networks is challenging because client-to-site mappings often misalign with operator's expectation due to opaque inter-domain routing. We present AnyPro, the first system to unlock the full potential of AS-path prepending (ASPP), efficiently deriving globally optimal configurations to steer clients toward performance-optimal sites at scale. AnyPro first employs an efficient polling mechanism to identify all clients sensitive to ASPP. By analyzing the routing changes during the process, the system derives a set of ASPP constraints that guide client traffic toward the desired sites. We then formulate the anycast optimization problem as a constraint-based program and compute optimal ASPP configurations. Extensive evaluation on a global testbed with 20 PoPs demonstrates the effectiveness of AnyPro: it reduces the 90th percentile latency by 37.7% compared to baseline configurations without ASPP. Furthermore, we show that AnyPro can be integrated with PoP-level anycast optimization techniques to achieve additional performance gains.