GeoNS

Geometric Large Scale Wireless Network Simulator

GeoNS is an open-source platform to simulate large-scale wireless networks. Contrary to the existing network simulators, which are location-transparent in their indexing, GeoNS uses location-dependent indexing in storing nodes of the network. In other words, we propose to view a wireless network as a spatial database, which allows us to use highly sophisticated spatial data structures in storing nodes of the network.

Run experiments in serial mode (helpful for debugging during development, or maybe sufficient for experiments).
Run experiments fully parallelized.
Synchronous or asynchronous reinforcement learning.
Reinforcement learning is implemented with the help of RLLib (see https://github.com/HerveFrezza-Buet/RLlib).
Modularity for easy modification / re-use of existing components.

Getting Started

Download Clone this repository to the local machine. You can use the git to clone or get the project via downloading the zip file.

$ git clone https://github.com/roamiri/GeoNS.git

Requirements Follow the instructions below to install the required packages to build GeoNS. (The platform is tested on LINUX Fedora 18, 30, and 31.)

$ dnf groupinstall 'C Development Tools and Libraries'
$ dnf install cmake boost boost-devel gsl gsl-devel python2 python2-devel numpy python2-matplotlib

Compilation Enter the GeoNS folder and follow the instructions below.

$ mkdir build
$ cd build
$ cmake ../CMakeLists.txt
$ make

Implemented Algorithms

There are three applications implemented in with the core of GeoNS. These applications are in three different folders as independent projects as path_selection, range_control, and clustering. If you do not wish to compile any of the applications, simply comment the respective line in the main CMakeLists file.

Distributed Path Selection in millimeter-wave IAB networks

We set the name of the application as pathSelection. In order to facilitate the simulation process, we provide an application programming interface (API) based on the LINUX command bash. Users can customize the API in the main function of the simulator. The defined API can be shown by using the --help flag as follow.

$ ./pathSelection --help
Allowed options:
  --help                Construct your network based on the following inputs.
  --dens arg            Density of the base stations, preference=1e-4 BS/1km2
  --fixed arg           Set wired BS implementation type (fixed(1) or variable(0))
  --count arg           Number of fixed wired base stations
  --prob arg            Wired nodes probability
  --policy arg          Path Selection Policy, options = HQF1, WF, PA, HQF2
  --if arg              Input file name
  --of arg              Output file name
  --svg arg             Topology SVG file name
  --iter arg            Number of iterations
  --verbose arg         verbose

Transmission range control in topology management of wireless sensor networks (WNSs)

Distributed clustering via message-passing (fast local clustering (floc))

Future Developments.

Overall the code is stable. I keep developing on the develop branch and the master branch is always stable. I am open to suggestions/contributions for other established algorithms to add or other developments to support more use cases. My next step is to add neural networks and backpropagation to the RL agents.

Visualization

The visualization of the network is done via simple SVG based outputs.

Acknowledgements

Thanks to Mola Pahnadayan who inspired me always as a true programmer.

Code dude! 👍