Combination of Scheduling and Dynamic Data Replication for Cloud Computing Workflows

Cloud computing is a powerful and high-capacity system, because it can satisfy various demands and share resources for users. It also to benefits from a capacity for treatment and unlimited storage. However, it is burdensome for the providers of internet services that the user demands are increasing as computer capacity is growing stronger and stronger. Therefore, the techniques of workflow scheduling and data replication are used to decrease the costs of the data intensive application. Unfortunately, these two approaches, which are very complementary, are used separately. In this article, a combination of workflow scheduling based on the clustering of data and dynamic data replication strategies has been introduced together. A Cloud simulator, Cloudsim, is used to evaluate the performance of the proposed algorithm. Simulation results show the effectiveness of the proposed algorithm in comparison with well-known algorithms such as random data placement and the Build Time algorithm.