Wireless Network simulator with Swarm Intelligence
Further images of the application
The purpose of this software to provide an opportonity to test various swarm intelligence (or other) based routing algorithms on Wireless Sensor Networks (WSN).
A WSN can be parameterized with the so called "global" parameters. A routing algorithm can have several so called "specific" parameters.
A routing algorihm must be a separate modul file, whose requirements can be found in the "modul_specification.txt" file. New moduls can be added by placing them to the "si_algs" subfolder. New moduls, which are already in the "si_algs" subfolder will be loaded at program startup, and new moduls can be loaded into the running appication by placing the modul file into the subfolder and then click on the "R" (refresh) button in the application.
Currently there are five built-in routing algorithm modul which can be used: four Ant Colony Optimization (ACO) based, and a not SI based algorithm: Dijkstra
Currently the Optimization button and the Batch run option do not do anything, these are placeholders for new features.
Built with the Qt framework. The callout chart example of Qt (python variant of this: https://doc.qt.io/qt-5/qtcharts-callout-example.html, which is in the Qt Python package "pyside2") was used, and the WNSI software includes a modified version of it.
Acknowledgement to emulbreh for the implemented Bridson algorithm: https://github.com/emulbreh/bridson/blob/master/bridson/__init__.py
Prerequisites:
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install PySide2:
pip install PySide2 -
install mpi4py:
python -m pip install mpi4py -
install numpy:
pip install numpy -
install an implementation of the Message Passing Interface (MPI) standard, for example OpenMPI or Microsoft MPI.
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in case of (Ubuntu) Linux, maybe necessary to install all libxcb tools too, like this:
sudo apt-get install libxcb*
If you downloaded the source files, you can run the application from the command line with this command:
mpiexec -n 1 python dm_program_v12.py