| Issue |
E3S Web Conf.
Volume 659, 2025
The 7th International Conference on Green Environmental Engineering and Technology (IConGEET2025)
|
|
|---|---|---|
| Article Number | 03004 | |
| Number of page(s) | 7 | |
| Section | Environmental Sustainability and Development | |
| DOI | https://doi.org/10.1051/e3sconf/202565903004 | |
| Published online | 20 November 2025 | |
Sustainable Data Placement Strategy for Energy-Efficient Cloud Storage and Enhanced Performance
1 Center for Software Technology and Management, Faculty of Information Science and Technology (FTSM), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia
2 Institute of Visual Informatics, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia
3 Faculty of Computer Science and Information Technology (FSKTM), Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia
* Corresponding author: marizuana.daud@ukm.edu.my
In cloud computing, data replication is essential for fault tolerance and data availability. However, many current methods overlook addressing green sustainability concerns, such as system performance and energy efficiency. In this paper, we propose a sustainable data placement strategy (SDPS) that strategically places replicas in cloud storage environments to optimize energy consumption, improve performance, and reduce carbon emissions in cloud storage environments. Specifically, our approach aims to improve response time and decrease replication time, two crucial performance metrics that contribute to a secure and eco-friendly environment. Using comparative experiments with CloudSim, we verified our approach by comparing it to well-known methods such as Dynamic Placement with Replica Selection (DPRS) and Replication Strategy using Data Center Selection Mechanism (RS-DCSM). Significant gains were shown by the experimental results, which included a reduction in average replication time of approximately 12% compared to DPRS and 24% compared to RS-DCSM. Comparatively, substantial improvement, 12% faster than DPRS and 22% quicker than RS-DCSM for average response time. Consequently, this research contributes to the field of green computing in cloud replication environments by efficiently reducing process overheads and preserving energy for sustainable ICT systems.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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