Marina Fomenkov

The 2nd Workshop on Active Internet Measurements (AIMS-2) Report

kc claffy, Emile Aben, Jordan Auge, Robert Beverly, Fabian Bustamante, Benoit Donnet, Timur Friedman, Marina Fomenkov, Peter Haga, Matthew Luckie, and Yuval Shavitt
Appears in: 
CCR October 2010

On February 8-10, 2010, CAIDA hosted the second Workshop on Active Internet Measurements (AIMS-2) as part of our series of Internet Statistics and Metrics Analysis (ISMA) workshops. The goals of this workshop were to further our understanding of the potential and limitations of active measurement research and infrastructure in the wide-area Internet, and to promote cooperative solutions and coordinated strategies to addressing future data needs of the network and security research communities.

The workshop on active internet measurements (AIMS) report

k. c. claffy, Marina Fomenkov, Ethan Katz-Bassett, Robert Beverly, Beverly A. Cox, and Matthew Luckie
Appears in: 
CCR October 2009

Measuring the global Internet is a perpetually challenging task for technical, economic and policy reasons, which leaves scientists as well as policymakers navigating critical questions in their field with little if any empirical grounding. On February 12-13, 2009, CAIDA hosted the Workshop on Active Internet Measurements (AIMS) as part of our series of Internet Statistics and Metrics Analysis (ISMA) workshops which provide a venue for researchers, operators, and policymakers to exchange ideas and perspectives.

A Day at the Root of the Internet

Sebastian Castro, Duane Wessels, Marina Fomenkov, and Kimberly Claffy
Appears in: 
CCR October 2008

We analyzed the largest simultaneous collection of full-payload packet traces from a core component of the global Internet infrastructure ever made available to academic researchers. Our dataset consists of three large samples of global DNS traffic collected during three annual 'Day in the Life of the Internet' (DITL) experiments in January 2006, January 2007, and March 2008.

The Workshop on Internet Topology (WIT) Report

Dmitri Krioukov, kc claffy, Marina Fomenkov, Fan Chung, Alessandro Vespignani, and Walter Willinger
Appears in: 
CCR January 2007

Internet topology analysis has recently experienced a surge of interest in computer science, physics, and the mathematical sciences. However, researchers from these different disciplines tend to approach the same problem from different angles. As a result, the field of Internet topology analysis and modeling must untangle sets of inconsistent findings, conflicting claims, and contradicting statements.

AS Relationships: Inference and Validation

Xenofontas Dimitropoulos, Dmitri Krioukov, Marina Fomenkov, Bradley Huffaker, Young Hyun, kc claffy, and George Riley
Appears in: 
CCR January 2007

Research on performance, robustness, and evolution of the global Internet is fundamentally handicapped without accurate and thorough knowledge of the nature and structure of the contractual relationships between Autonomous Systems (ASs). In this work we introduce novel heuristics for inferring AS relationships. Our heuristics improve upon previous works in several technical aspects, which we outline in detail and demonstrate with several examples. Seeking to increase the value and reliability of our inference results, we then focus on validation of inferred AS relationships.

Public Review By: 
Ernst Biersack

Inferring AS relationships using publicly available data is a difficult task for which various heuristics have been proposed. This paper revisits the problem, points out shortcomings of existing heuristics, and proposes improvements. The reviewers liked the paper for several reasons:

  • The paper does a nice job in reviewing the state of the art and improves on the existing heuristics.
  • The authors try to asses the quality of their inferences by contacting a small group ASs whom they asked for an explicit validation of the results. However, the sample size may be too small to allow any definite conclusions.
  • The heuristics proposed are implemented and the results of the AS inference made publicly available on a weekly basis. This should provide a basis on which further research can build on
    and compare its results against.

In summary, this paper combines existing and new heuristics for AS inference into a tool, the results of which are made available to the community.

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