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A bibliometric analysis: AI-driven data placement optimization in cloud replication environments


Citation

Mohd Ali, Fazlina and Mat Daud, Marizuana and Bahar, Nurhidayah and Mohd Salleh, Syahanim and Nor Rashid, Fadilla ‘Atyka and Md Yunus, Nur Arzilawati (2024) A bibliometric analysis: AI-driven data placement optimization in cloud replication environments. Journal of Informationsystem and Technology Management, 9 (37). pp. 86-97. ISSN 0128-1666

Abstract

Data placement strategy using artificial intelligence (AI) in cloud replication environments has garnered significant attention in recent years. Several studies have examined this area, aiming to enhance data replication techniques by integrating AI algorithms. There is still a minimum number of studies that have discovered the trending of the existing literature that reveals cloud replication leveraging artificial intelligence techniques in the current body of knowledge. This study explores this field's significance and relevance through a bibliometric analysis, particularly its integration with artificial intelligence (AI) techniques. The study highlights key trends and developments, highlighting the collaborative potential between cloud replication and AItechnologies. The outcome of this study contributes to practitioners and researchers in evaluating and identifying potential areas for future exploration in AI-driven data placement optimization in cloud replication environments


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Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.35631/jistm.937007
Publisher: Global Academic Excellence
Keywords: Artificial intelligence; Bibliometric; Loud computing; Data placement; Replication strategies
Depositing User: Ms. Nur Faseha Mohd Kadim
Date Deposited: 13 Jun 2025 03:59
Last Modified: 13 Jun 2025 03:59
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.35631/jistm.937007
URI: http://psasir.upm.edu.my/id/eprint/117851
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