Abstract
Cloud DBMS is a distributed database that delivers a query service across multiple distributed database nodes located in multiple data centers, including cloud data centers. MapReduce database provides business intelligence (BI) and fault tolerance, but does not directly support homogeneous data like parallel DBMS. Parallel DBMS is complex, efficient, but needs to restart a query upon failure. Hadoop implements MapReduce programming model, handles machine failures, and schedules intermachine communication while performing operations on large-scale datasets. With more and more cloud applications being available, data security also becomes an important issue in the cloud computing framework. This confidentiality requirement is essential when storage servers are owned by a cloud infrastructure provider (public cloud) and data are owned by other parties. In this paper, we propose a virtualized architecture for secure data management by combining parallel DBMS and MapReduce framework focusing on cloud DBMS properties to satisfy the requirements of current clouds.
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Singh, M., Singh, J. (2015). A Virtualized Architecture for Secure Database Management in Cloud Computing. In: Das, K., Deep, K., Pant, M., Bansal, J., Nagar, A. (eds) Proceedings of Fourth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 336. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2220-0_25
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DOI: https://doi.org/10.1007/978-81-322-2220-0_25
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