Federated Learning is a machine learning scheme in which a shared prediction model can
be collaboratively learned by a number of distributed nodes using their locally stored data. It
can provide better data privacy because training data are not transmitted to a central server.
Federated learning is well suited for edge computing applications and can leverage the the
computation power of edge servers and the data collected on widely dispersed edge
devices. To build such an edge federated learning system, we need to tackle a number of …