This is the code repository of our CNSM paper “Rescue: Inferring fine-grained traffic matrices via distributed deep residual networks".
Code is tested with Python=3.8.13. Install requirements with
pip -r install requirements/requirements.txt
Configure training settings for federated learning by editing config/federated.yml.
To run the ResCue code use the runner within the runners folder:
python runners/federated_runner.py
You can choose between multi-client or single-client trainings. When multi-client is set to true, multiple sequential threads are thrown setting an increasing number of clients - from client_range[0] to client_range[1] (see federated.yml). When multi-client is false, a thread will be thrown training a single federated model with the number of clients set as n_clients.
Before plotting, launch the evaluation script to compute the metrics obtained by the inference process.