AS Relationships: Inference and Validation
Xenofontas Dimitropoulos, Dmitri Krioukov, Marina Fomenkov, Bradley, Huffaker, Young Hyun, kc claffy, George Riley

TL;DR
This paper introduces improved heuristics for inferring AS relationships, validates them through surveys and BGP data comparison, and provides an accessible repository of annotated AS topology for research use.
Contribution
It presents novel heuristics for more accurate AS relationship inference and validates them with survey data, addressing limitations of existing BGP-based methods.
Findings
Achieved 96.5% accuracy for customer-provider relationships
Validated high accuracy of inferred relationships through surveys
Found BGP tables miss up to 86.2% of true AS adjacencies
Abstract
Research on performance, robustness, and evolution of the global Internet is fundamentally handicapped without accurate and thorough knowledge of the nature and structure of the contractual relationships between Autonomous Systems (ASs). In this work we introduce novel heuristics for inferring AS relationships. Our heuristics improve upon previous works in several technical aspects, which we outline in detail and demonstrate with several examples. Seeking to increase the value and reliability of our inference results, we then focus on validation of inferred AS relationships. We perform a survey with ASs' network administrators to collect information on the actual connectivity and policies of the surveyed ASs. Based on the survey results, we find that our new AS relationship inference techniques achieve high levels of accuracy: we correctly infer 96.5% customer to provider (c2p), 82.8%…
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Taxonomy
TopicsNetwork Traffic and Congestion Control · Caching and Content Delivery · Peer-to-Peer Network Technologies
