Abstract
Cloud computing has emerged as an extremely successful paradigm for deploying web applications. Scalability, elasticity, pay-per-use pricing, and economies of scale from large scale operations are the major reasons for the successful and widespread adoption of cloud infrastructures. Since a majority of cloud applications are data driven, database management systems (DBMSs) powering these applications form a critical component in the cloud software stack. In this article, we present an overview of our work on instilling these above mentioned “cloud features” in a database system designed to support a variety of applications deployed in the cloud: designing scalable database management architectures using the concepts of data fission and data fusion, enabling lightweight elasticity using low cost live database migration, and designing intelligent and autonomic controllers for system management without human intervention.
This work is partly funded by NSF grants III 1018637 and CNS 1053594 and an NEC Labs America University relations award.
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Agrawal, D., El Abbadi, A., Das, S., Elmore, A.J. (2011). Database Scalability, Elasticity, and Autonomy in the Cloud. In: Yu, J.X., Kim, M.H., Unland, R. (eds) Database Systems for Advanced Applications. DASFAA 2011. Lecture Notes in Computer Science, vol 6587. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20149-3_2
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DOI: https://doi.org/10.1007/978-3-642-20149-3_2
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