Data replication improvement strategy in cloud environments
Yunus Ahmed, Tushar Kumar Pandey and Dr. V Deeban Chakravarthy
Improving data replication procedures is critical for achieving the highest level of cost-effectiveness and data availability in a dynamic cloud computing environment. In this study, we provide an in-depth discussion of the D-RISC approach, which can assist in improving cloud-based data replication. This technology is referred to by the abbreviation D-RISC, which stands for Dynamic Replication with Intelligent Synchronization and Cost Optimization. The initial phase of the D-RISC approach incorporates critical characteristics such as data origin, access frequency, size, and relevance score. Following that, in order to inform its proactive replication decisions, it utilizes an Adaptive Analysis Engine, or AAE for short, to evaluate access patterns and anticipate peak loads and frequently accessed data. To conduct a full cost-benefit analysis, a cost optimization model (COM) may be constructed utilizing cloud billing data. Based on a variety of dynamic criteria, the Dynamic Replication Scheduler (DRS) determines if data should be duplicated, where it should be copied, and how many times it should be replicated. The consistency manager (CM) is in charge of keeping all copies in sync with each other in order to reduce latency and data discrepancies. Improving the AAE's potential use in future decision-making can be accomplished, for example, by implementing a feedback mechanism that gradually increases the model's accuracy. As a result, the AAE may grow more advantageous in the future.
How to cite this article:
Yunus Ahmed, Tushar Kumar Pandey and Dr. V Deeban Chakravarthy. Data replication improvement strategy in cloud environments. The Pharma Innovation Journal. 2023; 12(10S): 123-129.