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Energy Efficient Federated Learning Over Wireless Communication Networks · Around

2019

Energy Efficient Federated Learning Over Wireless Communication Networks

Yang, Zhaohui, Chen, Mingzhe, Saad, Walid et al.

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In this paper, the problem of energy efficient transmission and computation resource allocation for federated learning (FL) over wireless communication networks is investigated.

In the considered model, each user exploits limited local computational resources to train a local FL model with its collected data and, then, sends the trained FL model to a base station (BS) which aggregates the local FL model and broadcasts it back to all of the users.
Since FL involves an exchange of a learning model between users and the BS, both computation and communication latencies are determined by the learning accuracy level.
Meanwhile, due to the limited energy budget of the wireless users, both local computation energy and transmission energy must be considered during the FL process.

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