Data tiering for edge computers, hubs and central systems

A non-transitory computer readable medium comprising computer executable instructions that, when executed, perform a method for tiering data in a distributed data network, the method comprising:

• initiating a global model for tiering data in a distributed data network that includes a datacenter, hub servers, and edge servers;
• repeating until updates to a global model are less than a threshold:
• pushing the global model from a central system associated with the data center to each of first edge servers in the distributed data network, wherein the first edge servers are a subset of edge servers operating in the distributed data network and wherein the edge servers are closest to end user devices;
• training the global model at each of the first edge servers, wherein each of the first edge servers uses their own local data to train the global model;
• sending updates to the global model from the first edge servers to the central system;
• and
• updating the global model by the central system based on the updates.