Abstract
Cloud Computing is a mass platform to serve high volume data from multi-devices and numerous technologies. Cloud tenants have a high demand to access their data faster without any disruptions. Therefore, cloud providers are struggling to ensure every individual data is secured and always accessible. Hence, an appropriate replication strategy capable of selecting essential data is required in cloud replication environments as the solution. This paper proposed a Crucial File Selection Strategy (CFSS) to address poor response time in a cloud replication environment. A cloud simulator called CloudSim is used to conduct the necessary experiments, and results are presented to evidence the enhancement on replication performance. The obtained analytical graphs are discussed thoroughly, and apparently, the proposed CFSS algorithm outperformed another existing algorithm with a 10.47% improvement in average response time for multiple jobs per round.
Highlights
Cloud computing is a resilient and wellknown technology to serve enormous data from various platforms [1,2,3]
For 900 jobs, the results gradually improved by 7.33%, and for 1100 jobs, the improvement percentage is 3.23% for average response time
At the point of 1300 jobs, the Crucial File Selection Strategy (CFSS) algorithm depicted a 10.93% enhancement in response time compared to Dynamic Popularity aware Replication Strategy (DPRS)
Summary
Cloud computing is a resilient and wellknown technology to serve enormous data from various platforms [1,2,3]. The researcher overlooked the high replication time, which causes by the complex computation involved in the popular file selections. Hierarchical Data Replication Strategy (HDRS) can identify popular files based on the prediction of subsequent access data for data files in the cloud and replicate the replicas into the best site using network-level locality 29.
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