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arXiv · 1808.03949

Blockchained On-Device Federated Learning

Hyesung Kim·Jihong Park·Mehdi Bennis·Seong-Lyun Kim
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Abstract

By leveraging blockchain, this letter proposes a blockchained federated learning (BlockFL) architecture where local learning model updates are exchanged and verified. This enables on-device machine learning without any centralized training data or coordination by utilizing a consensus mechanism in blockchain. Moreover, we analyze an end-to-end latency model of BlockFL and characterize the optimal block generation rate by considering communication, computation, and consensus delays.

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Hyesung Kim, Jihong Park, Mehdi Bennis, Seong-Lyun Kim. 2019-07-01. Blockchained On-Device Federated Learning. https://arxiv.org/abs/1808.03949

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