Asynchronous Real-Time Federated Learning for Anomaly Detection in Microservice Cloud Applications

The complexity and dynamicity of microservice architectures in cloud environments present substantial challenges to the reliability and availability of the services built on these architectures. Therefore, effective anomaly detection is crucial to prevent impending failures and resolve them promptly...

Full description

Bibliographic Details

Published in:	IEEE Transactions on Machine Learning in Communications and Networking
Main Authors:	Mahsa Raeiszadeh, Amin Ebrahimzadeh, Roch H. Glitho, Johan Eker, Raquel A. F. Mini
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Subjects:	Anomaly detection distributed data federated learning microservice trace
Online Access:	https://ieeexplore.ieee.org/document/10835399/