twt-markovian-model

A Markovian model for multi-STA TWT configuration with general batch size distributions.

Installation

The project was developed with Python 3.12.12.

Install requirements using:

pip install -r requirements.txt

Make sure to create a results/ directory, as results will be written there as JSON.

scenario_params.py: define scenario parameters: traffic types and rates, maximum transmission rate, beacon interval duration...
batch_size_distributions.py: helper functions to obtain probability mass functions of batch distributions. Implemented: Poisson and Weibull
twt_markovian_model.py: implementation of the model, iterative procedure
run_model.py: run the model for a range of queue sizes and RP durations, write the results to JSON file
twt_configuration_algorithm.py: find an adequate TWT configuration with respect to QoS requirements (packet loss rate and mean packet delay) that minimizes energy consumption

Name		Name	Last commit message	Last commit date
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
batch_size_distribution.py		batch_size_distribution.py
requirements-algorithm.txt		requirements-algorithm.txt
requirements-model.txt		requirements-model.txt
requirements.txt		requirements.txt
run_model.py		run_model.py
scenario_params.py		scenario_params.py
twt_configuration_algorithm.py		twt_configuration_algorithm.py
twt_markovian_model.py		twt_markovian_model.py