Blockchain-based federated learning for securing internet of things: A comprehensive survey

W Issa, N Moustafa, B Turnbull, N Sohrabi… - ACM Computing …, 2023 - dl.acm.org
The Internet of Things (IoT) ecosystem connects physical devices to the internet, offering
significant advantages in agility, responsiveness, and potential environmental benefits. The …

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 …

The evolution of distributed systems for graph neural networks and their origin in graph processing and deep learning: A survey

J Vatter, R Mayer, HA Jacobsen - ACM Computing Surveys, 2023 - dl.acm.org
Graph neural networks (GNNs) are an emerging research field. This specialized deep
neural network architecture is capable of processing graph structured data and bridges the …

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 …

[HTML][HTML] Asynchronous federated learning on heterogeneous devices: A survey

C Xu, Y Qu, Y Xiang, L Gao - Computer Science Review, 2023 - Elsevier
Federated learning (FL) is a kind of distributed machine learning framework, where the
global model is generated on the centralized aggregation server based on the parameters of …

Federated learning for the internet of things: Applications, challenges, and opportunities

T Zhang, L Gao, C He, M Zhang… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
Billions of IoT devices will be deployed in the near future, taking advantage of faster Internet
speed and the possibility of orders of magnitude more endpoints brought by 5G/6G. With the …

Federated deep learning for cyber security in the internet of things: Concepts, applications, and experimental analysis

MA Ferrag, O Friha, L Maglaras, H Janicke… - IEEE Access, 2021 - ieeexplore.ieee.org
In this article, we present a comprehensive study with an experimental analysis of federated
deep learning approaches for cyber security in the Internet of Things (IoT) applications …

Blockchain-enabled federated learning: A survey

Y Qu, MP Uddin, C Gan, Y Xiang, L Gao… - ACM Computing …, 2022 - dl.acm.org
Federated learning (FL) has experienced a boom in recent years, which is jointly promoted
by the prosperity of machine learning and Artificial Intelligence along with emerging privacy …

Fusion of federated learning and industrial Internet of Things: A survey

P Boobalan, SP Ramu, QV Pham, K Dev, S Pandya… - Computer Networks, 2022 - Elsevier
Abstract Industrial Internet of Things (IIoT) lays a new paradigm for the concept of Industry
4.0 and paves an insight for new industrial era. Nowadays smart machines and smart …