LACeS: an Open, Fast, Responsible and Efficient Longitudinal Anycast Census System

Remi Hendriks, Matthew Luckie, Mattijs Jonker, Raffaele Sommese, Roland van Rijswijk-Deij

公開日: 2025/3/26

Abstract

IP anycast is a widely adopted technique in which an address is replicated at multiple locations, to, e.g., reduce latency and enhance resilience. Due to anycast's crucial role on the modern Internet, earlier research introduced tools to perform anycast censuses. The first, iGreedy, uses latency measurements from geographically dispersed locations to map anycast deployments. The second, MAnycast2, uses anycast to perform a census of other anycast networks. MAnycast2's advantage is speed, performing an Internet-wide census in 3 hours, but it suffers from problems with accuracy and precision. Inversely, iGreedy is highly accurate but much slower. On top of that, iGreedy has a much higher probing cost. In this paper we address the shortcomings of both systems and present LACeS (Longitudinal Anycast Census System). Taking MAnycast2 as a basis, we completely redesign its measurement pipeline, and add support for distributed probing, additional protocols (UDP, TCP and IPv6) and latency measurements similar to iGreedy. We validate LACeS on an anycast testbed with 32 globally distributed nodes, compare against an external anycast production deployment and extensive latency measurements with RIPE Atlas, and cross-check over 60% of detected anycast prefixes against operator ground truth. This shows that MAnycastR achieves high accuracy and precision. We make continual daily MAnycastR censuses available to the community and release the source code of the tool under a permissive open source license.

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