Unified ensemble federated learning with cloud computing for online anomaly detection in energy-efficient wireless sensor networks

Unified ensemble federated learning with cloud computing for online anomaly detection in energy-efficient wireless sensor networks

Abstract Anomaly detection in Wireless Sensor Networks (WSNs) is critical for their reliable and secure operation. Optimizing resource efficiency is crucial for reducing energy consumption. Two new algorithms developed for anomaly detection in WSNs—Ensemble Federated Learning (EFL) with Cloud Integr...

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Bibliographic Details
Main Authors: S. Gayathri, D. Surendran
Format: Article
Language:English
Published: SpringerOpen 2024-02-01
Series:Journal of Cloud Computing: Advances, Systems and Applications
Subjects:
Wireless sensor networks
Online anomaly detection
Energy efficiency
Federated learning
Machine learning
Cloud computing
Online Access:https://doi.org/10.1186/s13677-024-00595-y

Internet

https://doi.org/10.1186/s13677-024-00595-y

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