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
Scheduling of scientific workflow in non-dedicated heterogeneous multicluster platform
Journal of Systems and Software
Exploring Workflow Interoperability for Neuroimage Analysis on the SHIWA Platform
Journal of Grid Computing
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Recent advances in Internet and grid technologies have greatly enhanced scientific experiments' life cycle. In addition to compute- and data-intensive tasks, large-scale collaborations involving geographically distributed scientists and e-infrastructure are now possible. Scientific workflows, which encode the logic of experiments, are becoming valuable resources. Sharing these resources and letting scientists worldwide work together on one experiment is essential for promoting knowledge transfer and speeding up the development of scientific experiments. Here, the authors discuss the challenges involved in supporting collaborative e-Science experiments and propose support for different phases of the scientific experimentation life cycle.