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 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 …

Edge learning for B5G networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing

W Xu, Z Yang, DWK Ng, M Levorato… - IEEE journal of …, 2023 - ieeexplore.ieee.org
To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …

Wind power forecasting considering data privacy protection: A federated deep reinforcement learning approach

Y Li, R Wang, Y Li, M Zhang, C Long - Applied Energy, 2023 - Elsevier
In a modern power system with an increasing proportion of renewable energy, wind power
prediction is crucial to the arrangement of power grid dispatching plans due to the volatility …

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 …

A survey on security and privacy of federated learning

V Mothukuri, RM Parizi, S Pouriyeh, Y Huang… - Future Generation …, 2021 - Elsevier
Federated learning (FL) is a new breed of Artificial Intelligence (AI) that builds upon
decentralized data and training that brings learning to the edge or directly on-device. FL is a …

Federated learning: A survey on enabling technologies, protocols, and applications

M Aledhari, R Razzak, RM Parizi, F Saeed - IEEE Access, 2020 - ieeexplore.ieee.org
This paper provides a comprehensive study of Federated Learning (FL) with an emphasis
on enabling software and hardware platforms, protocols, real-life applications and use …

Federated learning for cybersecurity: Concepts, challenges, and future directions

M Alazab, SP RM, M Parimala… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Federated learning (FL) is a recent development in artificial intelligence, which is typically
based on the concept of decentralized data. As cyberattacks are frequently happening in the …

Fedml: A research library and benchmark for federated machine learning

C He, S Li, J So, X Zeng, M Zhang, H Wang… - arXiv preprint arXiv …, 2020 - arxiv.org
Federated learning (FL) is a rapidly growing research field in machine learning. However,
existing FL libraries cannot adequately support diverse algorithmic development; …

Blockchain-federated-learning and deep learning models for covid-19 detection using ct imaging

R Kumar, AA Khan, J Kumar, NA Golilarz… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
With the increase of COVID-19 cases worldwide, an effective way is required to diagnose
COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage …