Latency Analysis of Consortium Blockchained Federated Learning
This work addresses latency issues in federated learning for business applications, but it is incremental as it builds on existing methods with a specific focus on consortium blockchain.
The paper tackles the problem of analyzing latency in a decentralized federated learning system using consortium blockchain for business-to-business scenarios, and the result shows that their latency model effectively quantifies actual delays.
A decentralized federated learning architecture is proposed to apply to the Businesses-to-Businesses scenarios by introducing the consortium blockchain in this paper. We introduce a model verification mechanism to ensure the quality of local models trained by participators. To analyze the latency of the system, a latency model is constructed by considering the work flow of the architecture. Finally the experiment results show that our latency model does well in quantifying the actual delays.