Abstract: Since the past decades, the data replication trend has not subsided; it is progressing rapidly from multiple perspectives to enhance cloud replication performance. Researchers are eagerly focusing on improving the strategies in various perceptions; unfortunately, the vulnerability in every strategy is inevitable. A non-comprehensive replica strategy would have vulnerability and drawbacks. The drawbacks that usually reside in the developed strategies are not limited to high network usage, high process time, high response time, high storage consumption, and more, depending on the research areas. Many researchers are out of ideas to identify state-of-the-art issues. This exhaustive taxonomic study focused on analyzing the diversified contributions and limitations terrain of the cloud replication environment, focusing on data placement strategies. It seeks to delve deeply into its fundamental strategy, practical implementations, and the intricate challenges it poses. Concerning the imminent cloud-driven future, this structured review paper is a vital resource for researchers, policymakers, and industry professionals grappling with the complexities of this emerging paradigm. By illuminating the intricacies of data replication strategies, this study fosters a deeper appreciation for the transformative potential and the multifaceted challenges ahead of cloud data replications.

Fazlina Mohd Ali, Marizuana Mat Daud, Fadilla Atyka Nor Rashid, Nazhatul Hafizah Kamarudin, Syahanim Mohd Salleh and Nur Arzilawati Md Yunus, “A Taxonomic Study: Data Placement Strategies in Cloud Replication Environments” International Journal of Advanced Computer Science and Applications(IJACSA), 15(11), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0151182

@article{Ali2024,
title = {A Taxonomic Study: Data Placement Strategies in Cloud Replication Environments},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151182},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151182},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {11},
author = {Fazlina Mohd Ali and Marizuana Mat Daud and Fadilla Atyka Nor Rashid and Nazhatul Hafizah Kamarudin and Syahanim Mohd Salleh and Nur Arzilawati Md Yunus}
}