[HTML][HTML] Federated learning for secure IoMT-applications in smart healthcare systems: A comprehensive review

S Rani, A Kataria, S Kumar, P Tiwari - Knowledge-based systems, 2023 - Elsevier
Recent developments in the Internet of Things (IoT) and various communication
technologies have reshaped numerous application areas. Nowadays, IoT is assimilated into …

A state-of-the-art survey on solving non-iid data in federated learning

X Ma, J Zhu, Z Lin, S Chen, Y Qin - Future Generation Computer Systems, 2022 - Elsevier
Federated Learning (FL) proposed in recent years has received significant attention from
researchers in that it can enable multiple clients to cooperatively train global models without …

Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions

Q Duan, J Huang, S Hu, R Deng… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Full leverage of the huge volume of data generated on a large number of user devices for
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …

Federated learning for internet of things: A comprehensive survey

DC Nguyen, M Ding, PN Pathirana… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …

Federated learning in edge computing: a systematic survey

HG Abreha, M Hayajneh, MA Serhani - Sensors, 2022 - mdpi.com
Edge Computing (EC) is a new architecture that extends Cloud Computing (CC) services
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …

[HTML][HTML] Federated learning for IoT devices: Enhancing TinyML with on-board training

M Ficco, A Guerriero, E Milite, F Palmieri… - Information …, 2024 - Elsevier
The spread of the Internet of Things (IoT) involving an uncountable number of applications,
combined with the rise of Machine Learning (ML), has enabled the rapid growth of pervasive …

Federated learning for computationally constrained heterogeneous devices: A survey

K Pfeiffer, M Rapp, R Khalili, J Henkel - ACM Computing Surveys, 2023 - dl.acm.org
With an increasing number of smart devices like internet of things devices deployed in the
field, offloading training of neural networks (NNs) to a central server becomes more and …

Federated learning-empowered mobile network management for 5G and beyond networks: From access to core

J Lee, F Solat, TY Kim, HV Poor - … Communications Surveys & …, 2024 - ieeexplore.ieee.org
The fifth generation (5G) and beyond wireless networks are envisioned to provide an
integrated communication and computing platform that will enable multipurpose and …

Dynamic-fusion-based federated learning for COVID-19 detection

W Zhang, T Zhou, Q Lu, X Wang, C Zhu… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Medical diagnostic image analysis (eg, CT scan or X-Ray) using machine learning is an
efficient and accurate way to detect COVID-19 infections. However, the sharing of diagnostic …

Deep reinforcement learning assisted federated learning algorithm for data management of IIoT

P Zhang, C Wang, C Jiang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The continuous expanded scale of the industrial Internet of Things (IIoT) leads to IIoT
equipments generating massive amounts of user data every moment. According to the …