Energy-Efficient and Privacy-Preserved Incentive Mechanism for Mobile Edge Computing-Assisted Federated Learning in Healthcare System

• Published in: IEEE eTransactions on network and service management Vol. 21; no. 4; pp. 4801 - 4815
• Main Authors: Liu, Jingyuan, Chang, Zheng, Wang, Kai, Zhao, Zhiwei, Hamalainen, Timo
• Format: Journal Article
• Language: English
• Published: IEEE 01.08.2024
• Subjects: Computational modeling; Data models; Data privacy; energy efficiency; Federated learning; Games; healthcare; incentive mechanism; Medical services; mobile edge computing; power allocation; Privacy; privacy-preserving; Servers

Recent advancements in the Internet of Medical Things (IoMT) have significantly influenced the development of smart healthcare systems. Mobile edge computing (MEC)-assisted federated learning (FL) has emerged as a promising technology for providing fast, efficient, and reliable healthcare services w...