Tools for network tomography

networkTomography implements the methods developed and evaluated in Blocker and Airoldi (2011) and Airoldi and Blocker (2012). These include the authors' own dynamic multilevel model with calibration based upon a Gaussian state-space model in addition to implementations of the methods of Tebaldi & West (1998; Poisson-Gamma model with MCMC sampling), Zhang et al. (2002; tomogravity), Cao et al. (2000; Gaussian model with mean-variance relation), and Vardi (1996; method of moments). Data from the 1router network of Cao et al. (2000), the Abilene network of Fang et al. (2007), and the CMU network of Blocker and Airoldi (2011) are included for testing and reproducibility.


An R package for network tomography

networkTomography implements the methods developed and evaluated in Blocker and Airoldi (2011) and Airoldi and Blocker (2012). These include the authors' own dynamic multilevel model with calibration based upon a Gaussian state-space model in addition to implementations of the methods of Tebaldi and West (1998; Poisson-Gamma model with MCMC sampling), Zhang et al. (2002; tomogravity), Cao et al. (2000; Gaussian model with mean-variance relation), and Vardi (1996; method of moments). Data from the 1router network of Cao et al. (2000), the Abilene network of Fang et al. (2007), and the CMU network of Blocker and Airoldi (2011) are included for testing and reproducibility.

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("networkTomography")

0.3 by Alexander W Blocker, 13 years ago


https://github.com/awblocker/networkTomography


Browse source code at https://github.com/cran/networkTomography


Authors: Alexander W Blocker , Paul Koullick , Edoardo Airoldi


Documentation:   PDF Manual  


LGPL-2 license


Imports coda, igraph, KFAS, limSolve, plyr, Rglpk


Suggested by sand.


See at CRAN