A bibliometric analysis: AI-driven data placement optimization in cloud replication environments
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 stu...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Global Academic Excellence
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/117851/ http://psasir.upm.edu.my/id/eprint/117851/1/117851.pdf |
| _version_ | 1848867360473088000 |
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| author | Mohd Ali, Fazlina Mat Daud, Marizuana Bahar, Nurhidayah Mohd Salleh, Syahanim Nor Rashid, Fadilla ‘Atyka Md Yunus, Nur Arzilawati |
| author_facet | Mohd Ali, Fazlina Mat Daud, Marizuana Bahar, Nurhidayah Mohd Salleh, Syahanim Nor Rashid, Fadilla ‘Atyka Md Yunus, Nur Arzilawati |
| author_sort | Mohd Ali, Fazlina |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | 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 |
| first_indexed | 2025-11-15T14:35:16Z |
| format | Article |
| id | upm-117851 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:35:16Z |
| publishDate | 2024 |
| publisher | Global Academic Excellence |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1178512025-06-13T03:59:56Z http://psasir.upm.edu.my/id/eprint/117851/ A bibliometric analysis: AI-driven data placement optimization in cloud replication environments Mohd Ali, Fazlina Mat Daud, Marizuana Bahar, Nurhidayah Mohd Salleh, Syahanim Nor Rashid, Fadilla ‘Atyka Md Yunus, Nur Arzilawati 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 Global Academic Excellence 2024-12-11 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/117851/1/117851.pdf 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 https://gaexcellence.com/jistm/article/view/4434/4062 10.35631/jistm.937007 |
| spellingShingle | Mohd Ali, Fazlina Mat Daud, Marizuana Bahar, Nurhidayah Mohd Salleh, Syahanim Nor Rashid, Fadilla ‘Atyka Md Yunus, Nur Arzilawati A bibliometric analysis: AI-driven data placement optimization in cloud replication environments |
| title | A bibliometric analysis: AI-driven data placement optimization in cloud replication environments |
| title_full | A bibliometric analysis: AI-driven data placement optimization in cloud replication environments |
| title_fullStr | A bibliometric analysis: AI-driven data placement optimization in cloud replication environments |
| title_full_unstemmed | A bibliometric analysis: AI-driven data placement optimization in cloud replication environments |
| title_short | A bibliometric analysis: AI-driven data placement optimization in cloud replication environments |
| title_sort | bibliometric analysis: ai-driven data placement optimization in cloud replication environments |
| url | http://psasir.upm.edu.my/id/eprint/117851/ http://psasir.upm.edu.my/id/eprint/117851/ http://psasir.upm.edu.my/id/eprint/117851/ http://psasir.upm.edu.my/id/eprint/117851/1/117851.pdf |