[DMANET] MUSKETEER 1.0 - Tool for Multiscale Network Generation

Dear all,

We release a new network generation tool MUSKETEER (Multiscale Entropic
Network Generator). MUSKETEER generates highly realistic synthetic
network data for multiple domains. The tool has been validated in
domains such as epidemiological networks, social networks,
finite-element meshes, power grids as well as small-world and scale-free
networks. MUSKETEER takes empirical network data, which it coarsens and
then refines through the multiscale framework (V-cycle). During the
refinement phase, it introduces user-controlled perturbations which lead
to high-entropy changes of the original data. The problem of network
generation can be formulated at all levels of the multiscale hierarchy
(depending on the user's preferences to change the entire structure of
the network or only several particular scales). The proposed multiscale
framework can easily incorporate new features such as invariants that
have to be preserved in the generated network. MUSKETEER supports node
and edge attributes, and multiple network formats.

* Open source based on Python's NetworkX API
http://www.mcs.anl.gov/~safro/musketeer/

Link to preprint
http://arxiv.org/abs/1207.4266

We would appreciate your feedback on the multiscale strategy for network
generation and the software.

Alexander Gutfraind & Lauren A. Meyers, University of Texas at Austin
Ilya Safro, Argonne National Laboratory

--
Ilya Safro
Mathematics and Computer Science Division
Argonne National Laboratory
Phone: 1-630-252-5878
http://www.mcs.anl.gov/~safro

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