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RNet

Realistic random network generator

RNet is a realistic random network generator. It generates a social network from some statistical parameters. It deliberately assign a community to each node to achieve realistic social behavior.

RNet is highly flexible, it can accept several parameters. Besides the size of the generated network, it also accepts: outdegree, indegree and community size probability distributions, probability of connecting inside a node community and probability of connecting a node to a totally random node. These parameters make possible to generate a large variety of networks with much smaller restrictions than other generators.

RNet is also very fast, it is possible to generate graphs with millions of vertices in matter of seconds! It uses multithreading to better explore modern CPU power.

Examples

10000 node RNet*

Larger Image

10000 node RNet Data file**

* This network visualization was obtained using Gephi force atlas layout generator. Colors represent communities detected by "Fast Unfolding" Algorithm modularity algorithm and node size represent node Betweenness Centrality.

** This file was generated with RNet using default parameters Power Law distributions and default probabilities.

For more information go to our wiki.

Compilation

UnixLinux

Required

  • GCC The GNU Compiler Collection (GCC) is a compiler system produced by the GNU Project supporting various programming languages. GCC is a key component of the GNU toolchain.

  • OpenMP Support is required from the compiler, if you wish to use other compiler make sure it has OpenMP support.

  • Cmake is a cross-platform free software program for managing the build process of software using a compiler-independent method.

Optional:

  • CCMake is the CMake curses interface.

Commands:

# cd rnet/build
# cmake ../src (or ccmake ../src)
# make -j4
# ./rnet

Mac OS

Calling gcc in the command line actually calls for XCode's LLVM, which uses clang and does not currently support openMP. To compile you must first download a working version of gcc (with homebrew?) and set cmake to work with it:

CC=[path-to-gcc] CXX=[path-to-g++] cmake ../src

Windows

MinGW compiler is also compatible with RNet though, it needs to be properly installed. Some details should also be observed. For more information goto our Compile in Windows Wiki. Compiling in Cygwin, instead of compiling in native windows, is recommended.

References

Yet to appear

Disclaimer

RNet is still a prototype, it may undergo heavy changes along the academic publication process.

Usefull Links

  • CAMPS - Center for Analisys and Modeling of Systems Performance and Social Media

  • Get started with CMake! [1] [2]

  • Gephi, a great tool for graphs

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RNet - Realistic random network generator

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