A Survey of Data-Intensive Scientific Workflow Management |
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| Authors: | Ji Liu Esther Pacitti Patrick Valduriez Marta Mattoso |
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| Affiliation: | 1.MSR-Inria Joint Centre, Inria and LIRMM and University of Montpellier,Montpellier,France;2.Inria and LIRMM, University of Montpellier,Montpellier,France;3.COPPE/Federal University of Rio de Janeiro,Rio de Janeiro,Brazil |
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| Abstract: | Nowadays, more and more computer-based scientific experiments need to handle massive amounts of data. Their data processing consists of multiple computational steps and dependencies within them. A data-intensive scientific workflow is useful for modeling such process. Since the sequential execution of data-intensive scientific workflows may take much time, Scientific Workflow Management Systems (SWfMSs) should enable the parallel execution of data-intensive scientific workflows and exploit the resources distributed in different infrastructures such as grid and cloud. This paper provides a survey of data-intensive scientific workflow management in SWfMSs and their parallelization techniques. Based on a SWfMS functional architecture, we give a comparative analysis of the existing solutions. Finally, we identify research issues for improving the execution of data-intensive scientific workflows in a multisite cloud. |
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