AJAO, Ademolu Daniel and Jonathan, Oluranti and Adetiba, E. (2024) The Applications of Federated Learning Algorithm in the Federated Cloud Environment: A Systematic Review. In: International Conference on Science, Engineering and Business for Driving Sustainable Development Goals, 02-04 April 2024, Omu-Aran, Nigeria.
![[img]](http://eprints.covenantuniversity.edu.ng/style/images/fileicons/application_pdf.png) |
PDF
Download (89kB) |
Abstract
Federated learning (FL) refers to a system in which a central aggregator coordinates the efforts of several clients to solve the issues of machine learning. This setting allows the training data to be dispersed to protect the privacy of each device. This paper provides an overview of federated learning systems and how it can be applied in the federated cloud environment its frameworks, architectures, and applications, we were able to identify from various literature the Federated Learning technology was most used in the Federated Cloud/Multi-Cloud Environment, we also identified the use cases, additionally, we were able to identify the future directions Federated Learning could lean towards.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | nwokealisi |
| Date Deposited: | 07 Nov 2024 13:02 |
| Last Modified: | 07 Nov 2024 13:02 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/18569 |
Actions (login required)
 |
View Item |
