An Effective Structure for Data Management in the Cloud-Based Tools and Techniques
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Abstract
Through the management of cloud data for the tools and techniques, a solid framework will be developed which will efficiently handle the big-data and the heterogeneous datasets, which are characteristic to contemporary biological studies. This paper introduces a newly developed method of solving technical problems in the cloud computing system like storage, recovery, and analysis. The architecture is constructed in a way that allows for the addition of more nodes and advanced data management methods, such as distributed storage, data indexing, and query optimization, can be used to grant seamless access to the biological data. The key part is the centralized data storage and retrieval system built based on metadata indexing and under the principle of dynamic resources allocating for the simulations. Through performance assessments for the whole framework, we have demonstrated that the speed, resource utilization, as well as scalability are the outstanding ones over the conventional approach. This work gives us an interesting overview of the process of creating an efficient data solution for cloud-based organism research, which can be considered as a platform for advanced collaboration, innovation, and discovery within bioinformatics.
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