Prediction-based auto-scaling of scientific workflows
Proceedings of the 9th International Workshop on Middleware for Grids, Clouds and e-Science
Service level management for executable papers
Euro-Par'11 Proceedings of the 2011 international conference on Parallel Processing - Volume 2
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The amount of computing resources currently available on Clouds is large and easily available with pay per use cost model. E-Science applications that need on-demand execution benefit from Clouds, because no permanent computing resources to support peak demand has to be acquired. In this paper, we present AMOS, a system that automates creation and management of temporary Grids on a Cloud to execute (parts of) application workflows. We performed experiments with AMOS and a representative e-Science application on a research Grid and on the Amazon EC2 Cloud. The results show that AMOS is a viable approach to manage and execute e-Science applications in a flexible Grid environment and to explore novel mechanisms that allow optimal utilization of Cloud resources. Furthermore, we consider AMOS as a step towards an operating system for (virtual) infrastructures that enables Grid applications to control their computational resources at run-time.