Federated Learning-Based Failure Prediction with Distributed Data for Optical Networks

A federal learning-based failure prediction scheme is proposed for optical networks using the distributed practical data. Results show that the average prediction accuracy arrives to 94.15%, which is a comparable performance with the centralized model, but paying less communication cost and achieving better data privacy protection.