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Increasing the Accuracy of Federated Learning on Non-IID Scenarios using Client Clustering

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Author(s):
de Souza, Lucas Airam C. ; Camilo, Gustavo F. ; Campista, Miguel Elias M. ; Costa, Luis Henrique M. K.
Total Authors: 4
Document type: Journal article
Source: 2024 IEEE LATIN-AMERICAN CONFERENCE ON COMMUNICATIONS, LATINCOM; v. N/A, p. 6-pg., 2024-01-01.
Abstract

Federated Learning (FL) depends on the data distribution among the clients. FL struggles in scenarios with heterogeneous data collected by different clients, which reduces the model's accuracy. Hence, we propose a client clustering system to mitigate the convergence obstacles of federated learning in non-Independent and Identically Distributed (IID) scenarios. Our proposal identifies the clusters using a testing neural network model sent to clients as a probe. After a few training epochs, each client returns to the server a vector containing the last-layer weights of the obtained model. Thus, we save communication and computation resources compared with other clustering proposals that apply iterative methods or use the entire neural network model. We also evaluate three clustering algorithms: K-Means, DBSCAN, and OPTICS. The DBSCAN algorithm demonstrates better results, correctly identifying the clients' clusters in IID and non-IID data distributions. Finally, the results show that our system has a better classification performance than FedAVG, increasing its accuracy by approximately 16% on non-IID scenarios. (AU)

FAPESP's process: 15/24494-8 - Communications and processing of big data in cloud and fog computing
Grantee:Nelson Luis Saldanha da Fonseca
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 18/23292-0 - ACCRUE-SFI project: advanced collaborative research infrastructure for secure future internet
Grantee:Otto Carlos Muniz Bandeira Duarte
Support Opportunities: Regular Research Grants
FAPESP's process: 15/24485-9 - Future internet for smart cities
Grantee:Fabio Kon
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 14/50937-1 - INCT 2014: on the Internet of the Future
Grantee:Fabio Kon
Support Opportunities: Research Projects - Thematic Grants