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The Border Gateway Protocol (BGP) offers several knobs to control routing decisions, but they are coarse-grained and only affect routes received from neighboring Autonomous Systems (AS). To enhance policy expressiveness, BGP was extended with thecommunitiesattribute, allowing an AS to attach metadata to routes and influence the routing decisions of a remote AS. The metadata can carryinformationto (e.g., where a route was received) or request anactionfrom a remote AS (e.g., not to export a route to one of its neighbors). Unfortunately, the semantics of BGP communities are not standardized, lack universal rules, and are poorly documented. In this work, we design and evaluate algorithms to automatically uncover BGPaction communitiesand ASes that violate standard practices by consistently using theinformation communitiesof other ASes, revealing undocumented relationships between them (e.g., siblings). Our experimental evaluation with billions of route announcements from public BGP route collectors from 2018 to 2023 uncovers previously unknown AS relationships and shows that our algorithm for identifying action communities achieves average precision and recall of 92.5% and 86.5%, respectively. 

We describe the deployment of an Internet measurement experiment to three testbeds that offer Linux containers hosted at widely distributed vantage points: the well-established PlanetLab Central and PlanetLab Europe platforms, and the new EdgeNet platform. The experiment results were published in the proceedings of ACM IMC 2018. We compare the capabilities of each testbed and their effect on the ease of deployment of the experiment. Because the software for this experiment has several library dependencies and requires a recent compiler, it was easiest to deploy on EdgeNet, which is based on Docker and Kubernetes. This extended abstract is accompanied by a demonstration of the reproducible deployment of a measurement tool on EdgeNet.