Machine Learning-Based Anomaly Prediction for Proactive Monitoring in Data Centers: A Case Study on INFN-CNAF

Machine Learning-Based Anomaly Prediction for Proactive Monitoring in Data Centers: A Case Study on INFN-CNAF

Anomaly prediction in time series is crucial for ensuring the stability and security of data centers, especially in scientific contexts such as INFN-CNAF, the National Center for Research and Development in Information and Communication Technology of the National Institute for Nuclear Physics. At IN...

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Bibliographic Details
Main Authors: Andrea Asperti, Gabriele Raciti, Elisabetta Ronchieri, Daniele Cesini
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Applied Sciences
Subjects:
anomaly detection
anomaly prediction
predictive maintenance
time series
machine learning
Online Access:https://www.mdpi.com/2076-3417/15/2/655
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