Mobility Prediction and Resource-Aware Client Selection for Federated Learning in IoT

Mobility Prediction and Resource-Aware Client Selection for Federated Learning in IoT

This paper presents the Mobility-Aware Client Selection (MACS) strategy, developed to address the challenges associated with client mobility in Federated Learning (FL). FL enables decentralized machine learning by allowing collaborative model training without sharing raw data, preserving privacy. Ho...

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Bibliographic Details
Main Author: Rana Albelaihi
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Future Internet
Subjects:
federated learning
client selection
mobility prediction
dynamic IoT environments
Online Access:https://www.mdpi.com/1999-5903/17/3/109
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https://www.mdpi.com/1999-5903/17/3/109

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