AI-Drive Predicative Analysis for Datacentre Capacity Planning

Suraj, Patel (2022) AI-Drive Predicative Analysis for Datacentre Capacity Planning. Innovative: International Multi-disciplinary Journal of Applied Technology, 1 (2). pp. 22-30. ISSN 2995-486X

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Abstract

Datacenter capacity planning is a critical aspect of ensuring efficient resource utilization and minimizing operational costs. Traditional capacity planning methods rely on historical data and heuristic approaches, which may not be optimal in dynamic environments. This research paper explores the application of Artificial Intelligence (AI)-driven predictive analysis in datacenter capacity planning. By leveraging machine learning (ML) and deep learning models, predictive analysis can provide accurate demand forecasting, optimize resource allocation, and enhance datacenter efficiency. This paper reviews existing literature, proposes an AI-driven framework, and discusses challenges and future directions in predictive analytics for datacenter capacity planning.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	10 Apr 2025 01:52
Last Modified:	10 Apr 2025 01:52
URI:	http://eprints.umsida.ac.id/id/eprint/15733

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