Evolutionary Multiobjective Query Workload Optimization of Cloud Data Warehouses

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Provided by: Hindawi Publishing
Topic: Cloud
Format: PDF
With the advent of Cloud databases, query optimizers need to find pareto-optimal set of solutions in terms of response time and monetary cost. The authors' novel approach minimizes both objectives by deploying alternative virtual resources and query plans making use of the virtual resource elasticity of the Cloud. They propose an exact multi-objective branch-and-bound and a robust multi-objective genetic algorithm for the optimization of distributed data warehouse query workloads on the Cloud. In order to investigate the effectiveness of their approach, they incorporate the devised algorithms into a prototype system.
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