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Mkit: Internet Measurement arsenal for data inference and algorithms

Mkit is a consequence of the discussions at AIMS 2016 organised by CAIDA and this talk by Dr. Phillipa Gill. Mkit is a library that facilitates the use of measurement data and provides implementation of common old/new algorithms for Internet measurement data inference. It would implement the common denominator of tasks in terms of the tools the Internet measurement community uses in their everyday work.

Note: As of now, I write code for M-kit as and when my research allows me to, so you might find bugs. Feel free to fix them or open an issue so I can take a look at it!

As of now, we have APIs for the following:

  • RIPE Atlas meta-data (measurement and probes) processing ("Active IPV4 probes in UK?", "Active probes in AS174?")
  • Parsing RIPE traceroute data
  • Converting traceroute IP paths to AS paths (naive approach, working towards the one in Sidewalk Ends)
  • Handling IXP hops in traceroutes based on from recent PEERDINGDB data.
  • Running RIPE measurements (given probes IDs and destination IPs)
  • Parsing Iplane traceroutes to AS paths
  • CAIDA's pxf2as for IP->ASN mapping
  • MMind IP->ASN mapping

But we are actively working towards completing the APIs for parsing other datasets and your help is very welcome!

Common Datasets in Internet Measurement and related sub-domains

While this list is incomplete,

CAIDA Datasets

RIPE Atlas

Coming Soon!

AMP

API Features and Design Document (work in progress)

Feature set of Mkit document

Installation

  • python setup.py install

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