GitHub - ehsan5890/DefragDashboard: A dashboard for ECOC demonstration, This demonstration showcases the applicability and benefits of a deep reinforcement learning (DRL) agent for spectrum defragmentation in a realistic deployment. This is achieved by integrating the DRL agent with the operations of a carrier-grade optical network digital twin via standard T-API messages. · GitHub

Name		Name	Last commit message	Last commit date
.github/workflows		.github/workflows
.idea		.idea
assets		assets
deepdefrag		deepdefrag
defrag		defrag
gui		gui
static		static
tapi		tapi
tests		tests
todo		todo
.DS_Store		.DS_Store
.gitignore		.gitignore
README.md		README.md
app.py		app.py
dt_app.py		dt_app.py
dummy_script.py		dummy_script.py
fragmented_env.pickle		fragmented_env.pickle
layout_colorwidget.py		layout_colorwidget.py
multithread.py		multithread.py
pyproject.toml		pyproject.toml
requirements-test.in		requirements-test.in
requirements.in		requirements.in
requirements.txt		requirements.txt
setup.cfg		setup.cfg
test.ipynb		test.ipynb

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Installation

Make sure to use Python 3.10
Within the environment, install pip-tools
Compile the requirements file:

pip-compile requirements.in requirements-test.in -o requirements.txt

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A dashboard for ECOC demonstration, This demonstration showcases the applicability and benefits of a deep reinforcement learning (DRL) agent for spectrum defragmentation in a realistic deployment. This is achieved by integrating the DRL agent with the operations of a carrier-grade optical network digital twin via standard T-API messages.

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api digitaltwin reinforcement-learning tapi tapi-api

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