Understanding AS Relationships and Internet Routing Influence
Explore the complexities of AS relationships and their impact on Internet routing, including customer cones, AS validation, and associated caveats. Gain insights into measuring market power and network influence in the online landscape.
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Presentation Transcript
CAIDAs AS-rank: measuring the influence of ASes on Internet Routing Matthew Luckie Bradley Huffaker Amogh Dhamdhere Vasileios Giotsas k claffy http://as-rank.caida.org/
Overview 1. Inferring AS relationships using publicly available BGP paths views of ~400 ASes at Route Views and RIPE RIS 2. Inferring the influence of ASes based on their customer cone Traffic in your customer cone stays on-net and is the most profitable (when it reaches you) http://as-rank.caida.org/ 2
AS Relationships Validation Summary CAIDA: 2,370 2010 2012 83% p2p Most submitted via web form, some via email RPSL: 6,065 April 2012 100% p2c RIPE whois database, two-way handshake BGP Communities: 39,838 April 2012 59% p2c Dictionary of operator-published community meanings assembled by Vasileios Giotsas (UCL) Overall: 47,881 GT relationships, 63% p2c, 37% p2p ~38% of the publicly available graph. 3
AS Relationships - Validation p2c PPV 99.6% 99.0% 90.3% 90.6% 84.7% p2p PPV CAIDA UCLA Isolario Xia + Gao Gao SARK CSP ND-ToR 1/250 98.4% 1/100 90.9% 1/10 1/10 1/6.5 99.5% 1/63 1/12 1/25 1/23 1/200 96.0% 95.6% Take home: difficult to be accurate at inferring both types of relationships 4
Definition Customer Cones A s customer cone: A, B, C, D, E, F B s customer cone: B, E, F C s customer cone: C, D, E 5
Customer Cone Computation AS relationships are complex: two ASes may have a c2p relationship in one location, but p2p elsewhere Define customer cone based on provider/peer observed view of an AS A sees D and E as indirect customers via B, so B s customer cone only includes D, E from C. Might suffer from limited visibility A Region Y: Europe Region X: USA B B C NOT inferred to be part of B s. C F G H D E 6
Caveats AS Relationship ecosystem is complex Different relationships in different regions Can t differentiate between paid-peers and settlement-free peers (financial difference, not routing) Don t know about traffic Don t have much visibility into peering BGP paths are messy (poisoning, leaking) NOT a clear metric of market power 7
44% Level3 Level3 + GBLX Level3 (GBLX) Cogent Inteliquent TeliaSon. NTT Level3 + Genuity Tel. Italia TATA Sprint Verizon XO AT&T CL (QW) AboveNet CL (SV) Verizon Sprint MCI 9
Level3 Level3 (GBLX) Cogent Inteliquent Sprint Verizon AT&T (MCI/CL) 10
Customer cone as a metric Fraction: 0.75 TP Fraction: 0.25 P1 P2 VP A B C D What fraction of ASes in a customer cone are reached via the top provider? 11
Data Sharing On publication: 97% of Validation Data (not directly reported) 15 years of AS relationship inferences 15 years of customer cone inferences 14
