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 …

Federated learning for smart cities: A comprehensive survey

S Pandya, G Srivastava, R Jhaveri, MR Babu… - Sustainable Energy …, 2023 - Elsevier
With the advent of new technologies such as the Artificial Intelligence of Things (AIoT), big
data, fog computing, and edge computing, smart city applications have suffered from issues …

Federated machine learning: Survey, multi-level classification, desirable criteria and future directions in communication and networking systems

OA Wahab, A Mourad, H Otrok… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The communication and networking field is hungry for machine learning decision-making
solutions to replace the traditional model-driven approaches that proved to be not rich …

A comprehensive overview on 5G-and-beyond networks with UAVs: From communications to sensing and intelligence

Q Wu, J Xu, Y Zeng, DWK Ng… - IEEE Journal on …, 2021 - ieeexplore.ieee.org
Due to the advancements in cellular technologies and the dense deployment of cellular
infrastructure, integrating unmanned aerial vehicles (UAVs) into the fifth-generation (5G) and …

[HTML][HTML] Lead federated neuromorphic learning for wireless edge artificial intelligence

H Yang, KY Lam, L Xiao, Z Xiong, H Hu… - Nature …, 2022 - nature.com
In order to realize the full potential of wireless edge artificial intelligence (AI), very large and
diverse datasets will often be required for energy-demanding model training on resource …

[HTML][HTML] Computing in the sky: A survey on intelligent ubiquitous computing for uav-assisted 6g networks and industry 4.0/5.0

SH Alsamhi, AV Shvetsov, S Kumar, J Hassan… - Drones, 2022 - mdpi.com
Unmanned Aerial Vehicles (UAVs) are increasingly being used in a high-computation
paradigm enabled with smart applications in the Beyond Fifth Generation (B5G) wireless …

Privacy-preserving federated learning for UAV-enabled networks: Learning-based joint scheduling and resource management

H Yang, J Zhao, Z Xiong, KY Lam… - IEEE Journal on …, 2021 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) are capable of serving as flying base stations (BSs) for
supporting data collection, machine learning (ML) model training, and wireless …

[HTML][HTML] A review of AI-enabled routing protocols for UAV networks: Trends, challenges, and future outlook

A Rovira-Sugranes, A Razi, F Afghah, J Chakareski - Ad Hoc Networks, 2022 - Elsevier
Abstract Unmanned Aerial Vehicles (UAVs), as a recently emerging technology, enabled a
new breed of unprecedented applications in different domains. This technology's ongoing …

Dynamic edge association and resource allocation in self-organizing hierarchical federated learning networks

WYB Lim, JS Ng, Z Xiong, D Niyato… - IEEE Journal on …, 2021 - ieeexplore.ieee.org
Federated Learning (FL) is a promising privacy-preserving distributed machine learning
paradigm. However, communication inefficiency remains the key bottleneck that impedes its …