AMITÉ: Annotation and Mapping of Internet Topology at the Edges

Project Description

The AMITÉ ran from 2009 to 2012 and is now complete. This web page documents its accomplishments. For follow-on work, please see current work by the ANT Lab.

The goal of the AMITÉ research project is to develop new techniques, tools and datasets that provide a frequently-updated, edge-considering, annotated Internet topology. Unlike current work, our goal is to rapidly track Internet changes, to extend mapping as far to the Internet edges as possible, and to annotate the map with information about the network.

We expect that the resulting Internet mapping techniques and tools will be useful to understand other complex network topologies in greater detail. We expect that the maps themselves will be useful to other researchers to understand and improve network security and defenses, how the Internet is used, and how to better guide its evolution. We plan to make our data and tools available as possible through the PREDICT program and on request.

AMITÉ is a joint research effort of USC’s Information Sciences Institute and Computer Science Department , and part of the ANT: the Analysis of Network Traffic research group. It is supported by the US DHS CyberSecurity program through contract (number 09-C-0081).

People

  • Calvin Ardi, PhD student (USC CS Dept. and ISI)
  • Xun Fan, USC PhD graduate (2015) (USC CS Dept. and ISI)
  • Ramesh Govindan, co-PI on this project, professor (USC CS Dept.)
  • John Heidemann, PI on this project, project leader and professor (USC/ISI)
  • Zi Hu, USC CS MS graduate (2014) (USC/ISI)
  • Yuri Pradkin, researcher (USC/ISI)

Publications

  • Xun Fan, John Heidemann and Ramesh Govindan 2013. Evaluating Anycast in the Domain Name System. Proceedings of the IEEE Infocom (Turin, Italy, Apr. 2013), 1681–1689. [PDF] Details
  • John Heidemann and Walter Willinger 2013. Internet Visualization. Computing. 96, 1 (2013), 1–2. [DOI] [PDF] Details
  • Xue Cai, John Heidemann, Balachander Krishnamurthy and Walter Willinger 2012. An Organization-Level View of the Internet and its Implications (Extended). Technical Report ISI-TR-2009-679. USC/Information Sciences Institute. [PDF] Details
  • Xun Fan, John Heidemann and Ramesh Govindan 2012. Characterizing Anycast in the Domain Name System. Technical Report ISI-TR-2011-681. USC/Information Sciences Institute. [PDF] Details
  • Zi Hu and John Heidemann 2012. Towards Geolocation of Millions of IP Addresses. Proceedings of the ACM Internet Measurement Conference (Boston, MA, USA, 2012), 123–130. [DOI] [PDF] Details
  • Zi Hu and John Heidemann 2012. Towards Geolocation of Millions of IP Addresses. Technical Report ISI-TR-2012-680. USC/Information Sciences Institute. [PDF] Details
  • Xun Fan, John Heidemann and Ramesh Govindan 2011. Identifying and Characterizing Anycast in the Domain Name System. Technical Report ISI-TR-2011-671. USC/Information Sciences Institute. [PDF] Details
  • Xue Cai, John Heidemann, Balachander Krishnamurthy and Walter Willinger 2010. Towards an AS-to-Organization Map. Proceedings of the ACM Internet Measurement Conference (Melbourne, Australia, Nov. 2010), 199–205. [DOI] [PDF] Details
  • Xun Fan and John Heidemann 2010. Selecting Representative IP Addresses for Internet Topology Studies. Proceedings of the ACM Internet Measurement Conference (Melbourne, Australia, Nov. 2010), 411–423. [DOI] [PDF] Details
  • Xue Cai and John Heidemann 2010. Understanding Block-level Address Usage in the Visible Internet. Proceedings of the ACM SIGCOMM Conference (New Delhi, India, Aug. 2010), 99–110. [DOI] [PDF] Details
  • Xue Cai and John Heidemann 2010. Understanding Block-level Address Usage in the Visible Internet (extended). Technical Report ISI-TR-2009-665. USC/Information Sciences Institute. [PDF] Details
  • Xun Fan and John Heidemann 2010. Selecting Representative IP Addresses for Internet Topology Studies. Technical Report ISI-TR-2010-666. USC/Information Sciences Institute. [PDF] Details

For related publications, please see the ANT publications web page.

Software

  • IP Hitlist Generation We have developed a set of map/reduce processing scripts that run in Hadoop to consume our Internet address censuses and output hitlists. (This scripts depend on our internal Hadoop configuration and so will require some modification to work elsewhere, but we make them available and encourage feedback about their use.)
  • lonlat2color For geolocation of IP address maps we needed to convert (lon, lat) to color in HSL and RGB color schemes. We provide Perl and Python implementations.

See also the ANT software web page.

Datasets

  • Address Hitlists: An IP Address Space Hitlist is a list of IP addresses (representives) that cover the IPv4 address space. Our goal is to provide representatives that are responsive, complete and stable: that is, addresses that respond to pings and traceroutes (with high probability), that cover every allocated IPv4 /24 prefix, and that do not change much over time. For more information, please refer to our dataset page.