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FedKit: Enabling Cross-Platform Federated Learning for Android and iOS

Authors :
He, Sichang
Tang, Beilong
Zhang, Boyan
Shao, Jiaoqi
Ouyang, Xiaomin
Nugraha, Daniel Nata
Luo, Bing
Publication Year :
2024

Abstract

We present FedKit, a federated learning (FL) system tailored for cross-platform FL research on Android and iOS devices. FedKit pipelines cross-platform FL development by enabling model conversion, hardware-accelerated training, and cross-platform model aggregation. Our FL workflow supports flexible machine learning operations (MLOps) in production, facilitating continuous model delivery and training. We have deployed FedKit in a real-world use case for health data analysis on university campuses, demonstrating its effectiveness. FedKit is open-source at https://github.com/FedCampus/FedKit.<br />Comment: This work has been accepted for demonstration on IEEE International Conference on Computer Communications (INFOCOM) 2024

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2402.10464
Document Type :
Working Paper