Federated learning in edge computing: a systematic survey
Edge Computing (EC) is a new architecture that extends Cloud Computing (CC) services
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …
[HTML][HTML] Federated learning for secure IoMT-applications in smart healthcare systems: A comprehensive review
Recent developments in the Internet of Things (IoT) and various communication
technologies have reshaped numerous application areas. Nowadays, IoT is assimilated into …
technologies have reshaped numerous application areas. Nowadays, IoT is assimilated into …
Applications of federated learning; Taxonomy, challenges, and research trends
The federated learning technique (FL) supports the collaborative training of machine
learning and deep learning models for edge network optimization. Although a complex edge …
learning and deep learning models for edge network optimization. Although a complex edge …
Towards 6G-enabled internet of vehicles: Security and privacy
The conceptualisation of the sixth generation of mobile wireless networks (6G) has already
started with some potential disruptive technologies resonating as enablers for driving the …
started with some potential disruptive technologies resonating as enablers for driving the …
Privacy-preserving aggregation in federated learning: A survey
Over the recent years, with the increasing adoption of Federated Learning (FL) algorithms
and growing concerns over personal data privacy, Privacy-Preserving Federated Learning …
and growing concerns over personal data privacy, Privacy-Preserving Federated Learning …
On demand fog federations for horizontal federated learning in IoV
Federated learning using fog computing can suffer from the dynamic behavior of some of the
participants in its training process, especially in Internet-of-Vehicles where vehicles are the …
participants in its training process, especially in Internet-of-Vehicles where vehicles are the …
[HTML][HTML] FedSDM: Federated learning based smart decision making module for ECG data in IoT integrated Edge-Fog-Cloud computing environments
Massive data collection in modern systems has paved the way for data-driven machine
learning, a promising technique for creating reliable and robust statistical models. By …
learning, a promising technique for creating reliable and robust statistical models. By …
Combined federated and split learning in edge computing for ubiquitous intelligence in internet of things: State-of-the-art and future directions
Federated learning (FL) and split learning (SL) are two emerging collaborative learning
methods that may greatly facilitate ubiquitous intelligence in the Internet of Things (IoT) …
methods that may greatly facilitate ubiquitous intelligence in the Internet of Things (IoT) …
Decentralized federated learning for extended sensing in 6G connected vehicles
Research on smart connected vehicles has recently targeted the integration of vehicle-to-
everything (V2X) networks with Machine Learning (ML) tools and distributed decision …
everything (V2X) networks with Machine Learning (ML) tools and distributed decision …
Federated learning for edge computing: A survey
New technologies bring opportunities to deploy AI and machine learning to the edge of the
network, allowing edge devices to train simple models that can then be deployed in practice …
network, allowing edge devices to train simple models that can then be deployed in practice …