A Survey of Data-Intensive Scientific Workflow Management

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 pro- cess. 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 infrastruc- tures 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 ar- chitecture, 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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Article dans une revue
Journal of Grid Computing, Springer Verlag, 2015, 13, 44 p. 〈10.1007/s10723-015-9329-8〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01144760
Contributeur : Patrick Valduriez <>
Soumis le : mercredi 22 avril 2015 - 15:58:22
Dernière modification le : samedi 27 janvier 2018 - 01:30:41

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Ji Liu, Esther Pacitti, Patrick Valduriez, Marta Mattoso. A Survey of Data-Intensive Scientific Workflow Management. Journal of Grid Computing, Springer Verlag, 2015, 13, 44 p. 〈10.1007/s10723-015-9329-8〉. 〈lirmm-01144760〉

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