Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Combined Metrics Approach to Cloud Service Reliability using Artificial Intelligence

Version 1 : Received: 25 November 2021 / Approved: 29 November 2021 / Online: 29 November 2021 (15:39:23 CET)

How to cite: Chhetri, T.; Dehury, C.K.; Lind, A.; Srirama, S.N.; Fensel, A. A Combined Metrics Approach to Cloud Service Reliability using Artificial Intelligence. Preprints 2021, 2021110548 (doi: 10.20944/preprints202111.0548.v1). Chhetri, T.; Dehury, C.K.; Lind, A.; Srirama, S.N.; Fensel, A. A Combined Metrics Approach to Cloud Service Reliability using Artificial Intelligence. Preprints 2021, 2021110548 (doi: 10.20944/preprints202111.0548.v1).

Abstract

Identifying and anticipating potential failures in the cloud is an effective method for increasing cloud reliability and proactive failure management. Many studies have been conducted to predict potential failure, but none have combined SMART (Self-Monitoring, Analysis, and Reporting Technology) hard drive metrics with other system metrics such as CPU utilisation. Therefore, we propose a combined metrics approach for failure prediction based on Artificial Intelligence to improve reliability. We tested over 100 cloud servers’ data and four AI algorithms: Random Forest, Gradient Boosting, Long-Short-Term Memory, and Gated Recurrent Unit. Our experimental result shows the benefits of combining metrics, outperforming state-of-the-art.

Keywords

Failure Prediction; Fault-tolerance; Cloud Computing; Artificial Intelligence; Reliability

Subject

MATHEMATICS & COMPUTER SCIENCE, Artificial Intelligence & Robotics

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.