AI-based Proactive Storage Failure Management in Software-Defined Data Centres

Zhu, Y., How, K. C., Wu, H. J. and Cao, Q. (2023) AI-based Proactive Storage Failure Management in Software-Defined Data Centres. In: 6th International Conference on Information Science and Systems (ICISS 2023), Edinburgh, UK, August 11-13 2023, pp. 231-237. ISBN 9798400708206 (doi: 10.1145/3625156.3625190)

Abstract

Proactive failure management is essential to alleviate potential risks of service unavailability and downtime in Software-Defined Data Centres (SDDCs). Artificial Intelligence (AI) models enable proactive failure management by predicting and addressing potential failures before they actually occur. This paper proposes an AI-based Proactive Storage Failure Management (APSFM) solution for intelligent data centre management. The proposed solution includes a four-stage framework that employs AI models to predict failures efficiently. The study uses Random Forest and Artificial Neural Network models as examples to predict disk failures by employing Self-Monitoring, Analysis, and Reporting Technology (SMART) attributes. The experimental results have shown that both models can achieve high prediction performance.

• Item Type: Conference Proceedings
• Keywords: Storage Management, artificial Intelligence, failure prediction, Software-Defined Data Centre.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Cao, Dr Qi
• Authors: Zhu, Y., How, K. C., Wu, H. J., and Cao, Q.
• College/School: College of Science and Engineering > School of Computing Science
• ISBN: 9798400708206
• Copyright Holders: Copyright © 2023 Copyright held by the owner/author(s)
• First Published: First published in ICISS '23: Proceedings of the 2023 6th International Conference on Information Science and Systems
• Publisher Policy: Reproduced in accordance with the publisher copyright policy