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https://github.com/comnetshh/netsys2021-malene-code-release

Open source code release to replicate results of the conference paper.

https://github.com/comnetshh/netsys2021-malene-code-release

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
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    codemeta.json file
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    .zenodo.json file
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    DOI references
    Found 3 DOI reference(s) in README
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    Academic publication links
    Links to: zenodo.org
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    Academic email domains
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    Institutional organization owner
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    JOSS paper metadata
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    Scientific vocabulary similarity
    Low similarity (8.0%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Open source code release to replicate results of the conference paper.

Basic Info
  • Host: GitHub
  • Owner: ComNetsHH
  • License: gpl-3.0
  • Language: Python
  • Default Branch: main
  • Homepage: https://www.tuhh.de/comnets
  • Size: 47.9 KB
Statistics
  • Stars: 1
  • Watchers: 6
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created almost 5 years ago · Last pushed almost 5 years ago

https://github.com/ComNetsHH/netsys2021-malene-code-release/blob/main/ 

# Time- and Frequency-Domain Dynamic Spectrum Access: Learning Cyclic Medium Access Patterns in Partially Observable Environments
Open source code release for the publication at NetSys 2021, September 2021 in Lbeck, Germany.

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5195407.svg)](https://doi.org/10.5281/zenodo.5195407)


## Instructions
Each Python `.py` file performs a simulation and saves results into a corresponding `_data/.json` file. 
These are then parsed by the same Python script to create a graph in `_imgs/.pdf`.  
You can check each file for its command line parameters regarding the simulation, and you can also disable simulation or plotting.

The `Makefile` contains targets to re-create the graphs presented and discussed in the publication.
Please note that for the paper, a relatively large number of repetitions are performed to obtain statistically meaningful results.
However, this requires substantial simulation time. 
For a quicker first check, consider simulation just once or for a shorter time.

You can run `make all` to replicate all graphs from the paper in one command.

Owner

  • Name: Institute of Communication Networks
  • Login: ComNetsHH
  • Kind: organization
  • Location: Hamburg, Germany

Institute of Communication Networks (ComNets) at Hamburg University of Technology (TUHH)

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