Mixing Biases: Structural Changes in the AS Topology Evolution

In this paper we study the structural evolution of the AS topology as inferred from two different datasets over a period of seven years. We use a variety of topological metrics to analyze the structural differences revealed in the AS topologies inferred from the two different datasets. In particular, to focus on the evolution of the relationship between the core and the periphery, we make use of a recently introduced topological metric, the weighted spectral distribution. We find that the traceroute dataset has increasing difficulty in sampling the periphery of the AS topology, largely due to limitations inherent to active probing. Such a dataset has too limited a view to properly observe topological changes at the AS-level compared to a dataset largely based on BGP data. We also highlight limitations in current measurements that require a better sampling of particular topological properties of the Internet. Our results indicate that the Internet is changing from a core-centered, strongly customer-provider oriented, disassortative network, to a soft-hierarchical, peering-oriented, assortative network.

[1]  Andrew W. Moore,et al.  Weighted spectral distribution , 2008 .

[2]  Shi Zhou,et al.  Characterising and modelling the internet topology — The rich-club phenomenon and the PFP model , 2006 .

[3]  Almerima Jamakovic,et al.  On the importance of local connectivity for Internet topology models , 2009, 2009 21st International Teletraffic Congress.

[4]  M. Newman,et al.  Mixing patterns in networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[5]  Yuval Shavitt,et al.  A model of Internet topology using k-shell decomposition , 2007, Proceedings of the National Academy of Sciences.

[6]  Alessandro Vespignani,et al.  K-core decomposition of Internet graphs: hierarchies, self-similarity and measurement biases , 2005, Networks Heterog. Media.

[7]  Miguel Rio,et al.  Network topologies: inference, modeling, and generation , 2008, IEEE Communications Surveys & Tutorials.

[8]  Olaf Maennel,et al.  Testing the reachability of (new) address space , 2007, INM '07.

[9]  Amogh Dhamdhere,et al.  Ten years in the evolution of the internet ecosystem , 2008, IMC '08.

[10]  Michalis Faloutsos,et al.  On power-law relationships of the Internet topology , 1999, SIGCOMM '99.

[11]  Olaf Maennel,et al.  Bigfoot, sasquatch, the yeti and other missing links: what we don't know about the as graph , 2008, IMC '08.

[12]  Polly Huang,et al.  GEN02-3: On the Search of Internet AS-level Topology Invariants , 2006, IEEE Globecom 2006.

[13]  Nicholas Economides,et al.  The Economics of the Internet Backbone , 2005 .

[14]  M E J Newman Assortative mixing in networks. , 2002, Physical review letters.

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

[16]  Miguel Rio,et al.  Beyond Node Degree: Evaluating AS Topology Models , 2008, ArXiv.

[17]  Andrew W. Moore,et al.  Weighted Spectral Distribution for Internet Topology Analysis: Theory and Applications , 2010, IEEE/ACM Transactions on Networking.

[18]  Lixia Zhang,et al.  Observing the evolution of internet as topology , 2007, SIGCOMM 2007.

[19]  Randy H. Katz,et al.  Characterizing the Internet hierarchy from multiple vantage points , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[20]  Walter Willinger,et al.  In search of the elusive ground truth: the internet's as-level connectivity structure , 2008, SIGMETRICS '08.