Federated learning review: Fundamentals, enabling technologies, and future applications

S Banabilah, M Aloqaily, E Alsayed, N Malik… - Information processing & …, 2022 - Elsevier
Federated Learning (FL) has been foundational in improving the performance of a wide
range of applications since it was first introduced by Google. Some of the most prominent …

Smart contracts in blockchain technology: A critical review

H Taherdoost - Information, 2023 - mdpi.com
By utilizing smart contracts, which are essentially scripts that are anchored in a
decentralized manner on blockchains or other similar infrastructures, it is possible to make …

Edge artificial intelligence for 6G: Vision, enabling technologies, and applications

KB Letaief, Y Shi, J Lu, J Lu - IEEE Journal on Selected Areas …, 2021 - ieeexplore.ieee.org
The thriving of artificial intelligence (AI) applications is driving the further evolution of
wireless networks. It has been envisioned that 6G will be transformative and will …

Artificial intelligence for the metaverse: A survey

T Huynh-The, QV Pham, XQ Pham, TT Nguyen… - … Applications of Artificial …, 2023 - Elsevier
Along with the massive growth of the Internet from the 1990s until now, various innovative
technologies have been created to bring users breathtaking experiences with more virtual …

Blockchain-empowered federated learning: Challenges, solutions, and future directions

J Zhu, J Cao, D Saxena, S Jiang, H Ferradi - ACM Computing Surveys, 2023 - dl.acm.org
Federated learning is a privacy-preserving machine learning technique that trains models
across multiple devices holding local data samples without exchanging them. There are …

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 …

A survey on federated learning for resource-constrained IoT devices

A Imteaj, U Thakker, S Wang, J Li… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Federated learning (FL) is a distributed machine learning strategy that generates a global
model by learning from multiple decentralized edge clients. FL enables on-device training …

A comprehensive survey on blockchain in industrial internet of things: Motivations, research progresses, and future challenges

R Huo, S Zeng, Z Wang, J Shang… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
With rapid development of enabling technologies such as Internet of Things, robotics, and
big data, the fourth industrial revolution known as “Industry 4.0”(I4. 0) has become a great …

Federated learning meets blockchain in edge computing: Opportunities and challenges

DC Nguyen, M Ding, QV Pham… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Mobile-edge computing (MEC) has been envisioned as a promising paradigm to handle the
massive volume of data generated from ubiquitous mobile devices for enabling intelligent …

[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 …