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Mercury: Revealing Hidden Interconnections Between Access ISPs and Content Providers

  • Manuel Palacin
  • Alex Bikfalvi
  • Miquel Oliver
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8846)

Abstract

Knowing the detailed topology of the Internet at the Autonomous System (AS) level is extremely valuable for both researchers and industry when making network policies. Although there are many measurement projects and databases that provide this information, such as ARK, RETRO, ONO and PeeringDB, they only offer a partial view for analyzing end-to-end Internet routing paths and they do not focus on the hidden direct interconnections between Access ISPs and Content Providers. In order to address these shortcomings, we present Mercury, a web platform focused on the AS-level interconnection between content providers and content consumers. Mercury enables users to visualize the AS topology, aggregating data from traceroute measurements of participants and AS information from several databases. The advantage of Mercury is that it discovers how operators connect to other organizations and how content providers organize their server’s infrastructure (CDN) to reach their target audience. To this end, Mercury identifies Internet Exchange Points (IXPs) and AS relationships along an Internet path and presents this information via a web site and a built-in API. We evaluate its potential probing a dataset of 100 popular web URLs from the major Spanish ISPs and we successfully identify many direct interconnections that were hidden for other methodologies.

Keywords

Autonomous System Content Provider Content Delivery Cache Server Internet Topology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was partially supported by the Spanish government, through the project CISNETS (TEC2012-32354).

References

  1. 1.
    Ager, B., Mühlbauer, W., Smaragdakis, G., Uhlig, S.: Web content cartography. In: Proceedings of the 2011 ACM SIGCOMM Conference on Internet Measurement Conference, IMC ’11, pp. 585–600. ACM, New York (2011)Google Scholar
  2. 2.
    Alexa: Alexa top sites. http://www.alexa.com/topsites
  3. 3.
    Augustin, B., Krishnamurthy, B., Willinger, W.: IXPs: mapped? In: Proceedings of the 9th ACM SIGCOMM Internet Measurement Conference (IMC) (2009)Google Scholar
  4. 4.
    Augustin, B., Cuvellier, X., Orgogozo, B., Viger, F., Friedman, T., Latapy, M., Magnien, C., Teixeira, R.: Paris traceroute. http://www.paris-traceroute.net/
  5. 5.
    CAIDA: The CAIDA AS relationships dataset (2012). http://www.caida.org/data/active/as-relationships/
  6. 6.
    Calder, M., Fan, X., Hu, Z., Katz-Bassett, E., Heidemann, J., Govindan, R.: Mapping the expansion of google’s serving infrastructure. In: Proceedings of the 2013 Conference on Internet Measurement Conference, IMC (2013)Google Scholar
  7. 7.
    Chang, H., Govindan, R., Jamin, S., Shenker, S.J., Willinger, W.: Towards capturing representative AS-level internet topologies. In: Proceedings of ACM SIGMETRICS, pp. 280–281. ACM (2002)Google Scholar
  8. 8.
    Chen, K., Choffnes, D.R., Potharaju, R., Chen, Y., Bustamante, F.E., Pei, D., Zhao, Y.: Where the sidewalk ends: extending the Internet AS graph using traceroutes from P2P users. In: Proceedings of the 5th International Conference on Emerging Networking Experiments and Technologies (2009)Google Scholar
  9. 9.
    Dimitropoulos, X., Riley, G.: Modeling autonomous-system relationships. In: Proceedings of the 20th Workshop on Principles of Advanced and Distributed Simulation (PADS), pp. 143–149. IEEE Computer Society (2006)Google Scholar
  10. 10.
    He, Y., Siganos, G., Faloutsos, M., Krishnamurthy, S.: A systematic framework for unearthing the missing links: measurements and impact. In: Proceedings of 4th USENIX Symposium on Networked Systems Design and Implementation (NSDI), pp. 187–200. USENIX (2007)Google Scholar
  11. 11.
    Mao, Z.M., Rexford, J., Wang, J., Katz, R.H.: Towards an accurate AS-level traceroute tool. In: Proceedings of ACM SIGCOMM (2003)Google Scholar
  12. 12.
    MaxMind: GeoLite databases. http://dev.maxmind.com/geoip/legacy/geolite
  13. 13.
    Meyer, D.: University of Oregon Route Views. http://www.routeviews.org/
  14. 14.
    Oliveira, R.V., Zhang, B.: Observing the evolution of Internet AS topology. ACM SIGCOMM Comput. Commun. Rev. 37(4), 313–324 (2007)CrossRefGoogle Scholar
  15. 15.
  16. 16.
    Smith, P., Cisco Systems: BGP routing table. http://thyme.apnic.net/
  17. 17.
    Shavitt, Y., Shir, E.: DIMES: let the internet measure itself. ACM SIGCOMM Comput. Commun. Rev. 35(5), 71–74 (2005)CrossRefGoogle Scholar
  18. 18.
    Su, A.-J., Choffnes, D.R., Kuzmanovic, A., Bustamante, F.E.: Drafting behind Akamai: inferring network conditions based on CDN redirections. IEEE/ACM Trans. Network (TON) 17(6), 1752–1765 (2009)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Networking Technology and Strategies (NeTS) Research GroupUniversitat Pompeu Fabra (UPF)BarcelonaSpain

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