arXiv subjects

Remi Hendriks

Publications and source records attributed to Remi Hendriks.

3 recordsLinked to original sources

arXiv2026

Locating and Enumerating Anycast: a Comparison of Two Approaches

Anycast allows for providing services from multiple, geographically distant Points of Presence (PoPs), using a single IP address, to, e.g., improve resilience. Due to its opaqueness, it is often unknown which addresses are provisioned using anycast and, if so, where the PoPs are located. As anycast is widely used for critical Internet infrastructures (e.g., the DNS) efforts have been made to map anycast deployments. The current state-of-the-art mapping technique, iGreedy, relies on latency-based measurements, and is adversely affected by noise caused by, e.g., network processing delays. Previous work has shown that traceroute can alternatively be used to detect anycast. As traceroute reveals the hops a packet traverses, it may also be used to locate sites using geolocation data for hops near the anycast PoPs. This paper is the first to assess the performance of the traceroute-based approach at scale, by targeting 14k prefixes from an anycast census. Using ground truth we show traceroute achieves a slight increase in enumeration and geolocation precision over iGreedy. However, it suffers from overestimating the number of PoPs and incurs a 4 times increase in probing cost, making it unattractive for anycast censuses.

cs.NI↗

arXiv2025

Load-Balancing versus Anycast: A First Look at Operational Challenges

Load Balancing (LB) is a routing strategy that increases performance by distributing traffic over multiple outgoing paths. In this work, we introduce a novel methodology to detect the influence of LB on anycast routing, which can be used by operators to detect networks that experience anycast site flipping, where traffic from a single client reaches multiple anycast sites. We use our methodology to measure the effects of LB-behavior on anycast routing at a global scale, covering both IPv4 and IPv6. Our results show that LB-induced anycast site flipping is widespread. The results also show our method can detect LB implementations on the global Internet, including detection and classification of Points-of-Presence (PoP) and egress selection techniques deployed by hypergiants, cloud providers, and network operators. We observe LB-induced site flipping directs distinct flows to different anycast sites with significant latency inflation. In cases with two paths between an anycast instance and a load-balanced destination, we observe an average RTT difference of 30 ms with 8% of load-balanced destinations seeing RTT differences of over 100 ms. Being able to detect these cases can help anycast operators significantly improve their service for affected clients.

cs.NI↗

arXiv2025

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

IP anycast replicates an address at multiple locations to reduce latency and enhance resilience. Due to anycast's crucial role in 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 and coverage but suffers from problems with accuracy, while iGreedy is highly accurate but slower using author-defined probing rates and costlier. 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 (DNS over UDP, TCP SYN/ACK, 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, extensive latency measurements with RIPE Atlas and cross-check over 60% of detected anycast using operator ground truth that shows LACeS achieves high accuracy. Finally, we provide a longitudinal analysis of anycast, covering 17+ months, showing LACeS achieves high precision. We make continual daily LACeS censuses available to the community and release the source code of the tool under a permissive open source license.

cs.NI↗