Abstract
The Cloud Computing systems are in the process of becoming an important platform for scientific applications. Optimization problems of data placement and task scheduling in a heterogeneous environment such as cloud are difficult problems. Approaches for scheduling and data placement is often highly correlated, which take into account a few factors at the same time, and what are the most often adapted to applications data medium and therefore goes not to scale. The objective of this work is to propose an optimization approach that takes into account an effective data placement and scheduling of tasks by replication in Cloud environments.
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