Using peeringDB to understand the peering ecosystem

In this study we mine one of the few sources of public data available about the interdomain peering ecosytem: PeeringDB [1], an online database where participating networks contribute information about their peering policies, traffic volumes and presence at various geographic locations. Although established to support the practical needs of operators, this data also provides a valuable source of information to researchers. Using BGP data to cross-validate three years of PeeringDB snapshots, we find that PeeringDB membership is reasonably representative of the Internet's transit, content, and access providers in terms of business types and geography of participants, and PeeringDB data is generally up-to-date. We find strong correlations among different measures of network size -- BGP-advertised address space, PeeringDB-reported traffic volume and presence at peering facilities, and between these size measures and advertised peering policies.

[1]  Jessica L. Beyer.  The Pirate Bay , 2014 .

[2]  Dmitri V. Krioukov,et al.  Revealing the Autonomous System Taxonomy: The Machine Learning Approach , 2006, ArXiv.

[3]  Amogh Dhamdhere,et al.  The Internet is flat: modeling the transition from a transit hierarchy to a peering mesh , 2010, CoNEXT.

[4]  Amogh Dhamdhere,et al.  Open peering by Internet transit providers: Peer preference or peer pressure? , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[5]  Zongpeng Li,et al.  The Flattening Internet Topology: Natural Evolution, Unsightly Barnacles or Contrived Collapse? , 2008, PAM.

[6]  Amogh Dhamdhere,et al.  Peering strategy adoption by transit providers in the internet: a game theoretic approach? , 2012, PERV.

[7]  Vasileios Giotsas,et al.  Inferring multilateral peering , 2013, CoNEXT.

[8]  Amogh Dhamdhere,et al.  Twelve Years in the Evolution of the Internet Ecosystem , 2011, IEEE/ACM Transactions on Networking.

[9]  Amogh Dhamdhere,et al.  GENESIS: An agent-based model of interdomain network formation, traffic flow and economics , 2012, 2012 Proceedings IEEE INFOCOM.

[10]  Anja Feldmann,et al.  Anatomy of a large european IXP , 2012, SIGCOMM '12.

[11]  Farnam Jahanian,et al.  Internet inter-domain traffic , 2010, SIGCOMM '10.

[12]  Petter Holme,et al.  An integrated model of traffic, geography and economy in the internet , 2008, CCRV.

[13]  David C. Parkes,et al.  An Economically-Principled Generative Model of AS Graph Connectivity , 2009, IEEE INFOCOM 2009.

[14]  Lixia Zhang,et al.  The (In)Completeness of the Observed Internet AS-level Structure , 2010, IEEE/ACM Transactions on Networking.

[15]  Amogh Dhamdhere,et al.  Analysis of peering strategy adoption by transit providers in the Internet , 2012, 2012 Proceedings IEEE INFOCOM Workshops.

[16]  Vasileios Giotsas,et al.  AS relationships, customer cones, and validation , 2013, Internet Measurement Conference.

[17]  Brice Augustin,et al.  IXPs: mapped? , 2009, IMC '09.

[18]  Walter Willinger,et al.  To Peer or Not to Peer: Modeling the Evolution of the Internet's AS-Level Topology , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.