Multi-factor replica placement strategy for resource failure extenuation in cloud replication environment
Cloud replication strategies have become an evolving technology for managing the growing volume and variety of data in cloud storage. Delay in data access and data loss can affect overall system performance, which is why cloud providers often rely on replication strategies to store multiple copies o...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Institute of Electrical and Electronics Engineers
2025
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/124854/1/124854.pdf http://psasir.upm.edu.my/id/eprint/124854/ https://ieeexplore.ieee.org/document/11218838/ |
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| Summary: | Cloud replication strategies have become an evolving technology for managing the growing volume and variety of data in cloud storage. Delay in data access and data loss can affect overall system performance, which is why cloud providers often rely on replication strategies to store multiple copies of data in different locations. This approach ensures the availability of multiple data copies, swift responses, and fault resilience while maintaining costs that are affordable for both users and providers. The main challenges in cloud replication strategies are to ensure data is continuously accessible while reducing network consumption. To prevent such issues, an effective replication strategy needs to be established in a cloud environment to enhance overall performance. This study presents a novel Multi-Factor Replica Placement Strategy (MRPS) that effectively reduces the risk of resource failure in cloud replication systems. The performance of the suggested algorithm was evaluated through a comprehensive experiment using the CloudSim simulator, and its ability to choose and replicate data files for user requests was measured. On average, MRPS achieved 16% more data availability compared to DPRS and 17% compared to RS-DCSM. Meanwhile, there is a 26% improvement in network usage by MRPS, surpassing DPRS, and a 23% improvement, surpassing RS-DCSM. These results provide strong evidence of the success of the proposed MRPS and improved performance. By surmounting the problems associated with data replication in cloud environments, this research seeks to provide valuable contributions to replica placement strategies. |
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