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Volume 19, Issue 1
  • ISSN: 1872-2121
  • E-ISSN: 2212-4047

Abstract

Background

Cloud services have become a popular approach for offering efficient services for a wide range of activities. Predicting hardware failures in a cloud data center can minimize downtime and make the system more reliable and fault-tolerant.

Objective

This research aims to analyze a predictive hardware failure model based on machine learning that anticipates the required remediations for undiagnosed failures in a cloud computing system serving multiclass requests.

Methods

The model is tested on a carefully designed cloud data center that categorizes incoming requests as web, compute, storage, and dedicated server requests. To demonstrate improved reliability, a carefully designed test case is run on ReliaCloud-NS, which is a simulator for creating a CCS and computing its reliability.

Results

The work found that using this model considerably enhanced the reliability of cloud computing systems when compared to not using the model.

Conclusion

Although various estimation methods are patented to evaluate the system reliability of a cloud computing network, the emphasis of this study was mostly on improving the reliability of request-segregated clouds upon failing hardware resources like CPU, memory, bandwidth, and hard disc. Moreover, the prediction model might potentially be expanded to other system resources such as GPUs, software, and database packages.

© 2025 Bentham Science Publishers
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/content/journals/eng/10.2174/0118722121260903231009104614
2025-01-01
2024-11-26

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/content/journals/eng/10.2174/0118722121260903231009104614
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Evaluation of Reliability in Request-segregated Clouds through Remiadiations Predicting Hardware Failure Scheme
Recent Pat Eng 19, E161023222245 (2025); https://doi.org/10.2174/0118722121260903231009104614
/content/journals/eng/10.2174/0118722121260903231009104614
/content/journals/eng/10.2174/0118722121260903231009104614
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  • Article Type:     Research Article
Keyword(s): annual failure rate (AFR); Cloud computing system (CCS); hardware failure scheme; monte carlo simulation (MCS); request-segregated clouds; virtual machines (VM)

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