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Federated learning‐based IoT: A systematic literature review.
- Source :
- International Journal of Communication Systems; 7/25/2022, Vol. 35 Issue 11, p1-23, 23p
- Publication Year :
- 2022
-
Abstract
- Summary: The Internet of Things (IoT) has a significant impact on our daily lives as applications, services, devices, and industries become more intelligent. Artificial intelligence (AI) is expected to significantly influence machine learning training on IoT devices without data sharing. Federated learning (FL) is a distributed machine learning method used in many IoT smart devices; however, FL ensures IoT security and privacy. The systematic literature review (SLR) method is used in this paper to review recently published articles in the FL‐based IoT domain. We analyzed 39 papers that were published between 2018 and March 2022. According to the evaluation factors, the accuracy factor has a high percentage in the FL‐based IoT domain by 29%, and the epoch has 23%, the time has 18%, the energy consumption has 9%, the delay has 9%, the communication overhead has 6%, and the privacy has 6%. Finally, we discuss future research challenges and open issues in the context of FL‐based IoT. [ABSTRACT FROM AUTHOR]
- Subjects :
- INTERNET of things
ARTIFICIAL intelligence
ELECTRIC machines
INFORMATION sharing
Subjects
Details
- Language :
- English
- ISSN :
- 10745351
- Volume :
- 35
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- International Journal of Communication Systems
- Publication Type :
- Academic Journal
- Accession number :
- 157461982
- Full Text :
- https://doi.org/10.1002/dac.5185