The twofold nature of autonomous systems: Evidence combining stock market data with topological properties

Autonomous Systems (AS) exist and co-exist in two parallel dimensions. In one dimension they are physical networks, whose interconnections are necessary to ensure global Internet reachabilty. In the other dimension, ASes are large well-known companies competing in the same industry. In this paper we bridge together these dimensions by investigating synchronous cross correlations of stock market data and AS-level topological properties. We find that geographically close companies offering similar services are driven by common economic factors. We also provide evidence on the existence and nature of factors governing AS global as well as local topological properties.

[1]  Yao Zhao,et al.  Where the Sidewalk Ends: Extending the Internet AS Graph Using Traceroutes from P2P Users , 2014, IEEE Trans. Computers.

[2]  Enrico Gregori,et al.  On the feasibility of measuring the internet through smartphone-based crowdsourcing , 2012, 2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt).

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

[4]  Walter Willinger,et al.  10 Lessons from 10 Years of Measuring and Modeling the Internet's Autonomous Systems , 2011, IEEE Journal on Selected Areas in Communications.

[5]  Chiara Orsini,et al.  k-dense communities in the internet AS-level topology , 2011, 2011 Third International Conference on Communication Systems and Networks (COMSNETS 2011).

[6]  Xiaoming Wang,et al.  Understanding and Modeling the Internet Topology: Economics and Evolution Perspective , 2010, IEEE/ACM Transactions on Networking.

[7]  Yuval Shavitt,et al.  On the feasibility of a large scale distributed testbed for measuring quality of path characteristics in the Internet , 2009, 2009 5th International Conference on Testbeds and Research Infrastructures for the Development of Networks & Communities and Workshops.

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

[9]  WillingerWalter,et al.  In search of the elusive ground truth , 2008 .

[10]  Rami Cohen,et al.  The Internet Dark Matter - on the Missing Links in the AS Connectivity Map , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[11]  Priya Mahadevan,et al.  Lessons from Three Views of the Internet Topology , 2005, ArXiv.

[12]  Massimo Marchiori,et al.  Error and attacktolerance of complex network s , 2004 .

[13]  M. Newman,et al.  Origin of degree correlations in the Internet and other networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  R Pastor-Satorras,et al.  Dynamical and correlation properties of the internet. , 2001, Physical review letters.

[15]  Rosario N. Mantegna,et al.  Book Review: An Introduction to Econophysics, Correlations, and Complexity in Finance, N. Rosario, H. Mantegna, and H. E. Stanley, Cambridge University Press, Cambridge, 2000. , 2000 .

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

[17]  FaloutsosMichalis,et al.  On power-law relationships of the Internet topology , 1999 .

[18]  R. Mantegna.  Hierarchical structure in financial markets , 1998, cond-mat/9802256.

[19]  J. Rodgers,et al.  Thirteen ways to look at the correlation coefficient , 1988 .

[20]  G. Toulouse,et al.  Ultrametricity for physicists , 1986 .

[21]  W. R. Buckland.  Outliers in Statistical Data , 1979 .

[22]  J. Gower,et al.  Minimum Spanning Trees and Single Linkage Cluster Analysis , 1969 .

[23]  Balachander Krishnamurthy,et al.  A Socratic method for validation of measurement-based networking research , 2011, Comput. Commun..

[24]  W. Norton.  The Evolution of the U.S. Internet Peering Ecosystem , 2003 .

[25]  W. Norton,et al.  Internet Service Providers and Peering , 2001 .

[26]  R. Mantegna,et al.  An Introduction to Econophysics: Contents , 1999 .

[27]  Robin Sibson,et al.  SLINK: An Optimally Efficient Algorithm for the Single-Link Cluster Method , 1973, Comput. J..