6G Internet of Things: A comprehensive survey

DC Nguyen, M Ding, PN Pathirana… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The sixth-generation (6G) wireless communication networks are envisioned to revolutionize
customer services and applications via the Internet of Things (IoT) toward a future of fully …

Recent advances on federated learning for cybersecurity and cybersecurity for federated learning for internet of things

B Ghimire, DB Rawat - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Decentralized paradigm in the field of cybersecurity and machine learning (ML) for the
emerging Internet of Things (IoT) has gained a lot of attention from the government …

Holistic network virtualization and pervasive network intelligence for 6G

X Shen, J Gao, W Wu, M Li, C Zhou… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …

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 comprehensive survey of privacy-preserving federated learning: A taxonomy, review, and future directions

X Yin, Y Zhu, J Hu - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
The past four years have witnessed the rapid development of federated learning (FL).
However, new privacy concerns have also emerged during the aggregation of the …

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 survey on federated learning

C Zhang, Y Xie, H Bai, B Yu, W Li, Y Gao - Knowledge-Based Systems, 2021 - Elsevier
Federated learning is a set-up in which multiple clients collaborate to solve machine
learning problems, which is under the coordination of a central aggregator. This setting also …

Survey on 6G frontiers: Trends, applications, requirements, technologies and future research

C De Alwis, A Kalla, QV Pham, P Kumar… - IEEE Open Journal …, 2021 - ieeexplore.ieee.org
Emerging applications such as Internet of Everything, Holographic Telepresence,
collaborative robots, and space and deep-sea tourism are already highlighting the …

Evolution of NOMA toward next generation multiple access (NGMA) for 6G

Y Liu, S Zhang, X Mu, Z Ding, R Schober… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
Due to the explosive growth in the number of wireless devices and diverse wireless
services, such as virtual/augmented reality and Internet-of-Everything, next generation …

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 …