caa a22 4500 606244824 CHVBK 20210128101332.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s10723-015-9329-8 doi (NATIONALLICENCE)springer-10.1007/s10723-015-9329-8 A Survey of Data-Intensive Scientific Workflow Management [Elektronische Daten] [Ji Liu, Esther Pacitti, Patrick Valduriez, Marta Mattoso] 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. Springer Science+Business Media Dordrecht, 2015 Scientific workflow nationallicence Scientific workflow management system nationallicence Grid nationallicence Cloud nationallicence Multisite cloud nationallicence Distributed and parallel data management nationallicence Scheduling nationallicence Parallelization nationallicence Liu Ji MSR-Inria Joint Centre, Inria and LIRMM and University of Montpellier, Montpellier, France aut Pacitti Esther Inria and LIRMM, University of Montpellier, Montpellier, France aut Valduriez Patrick MSR-Inria Joint Centre, Inria and LIRMM and University of Montpellier, Montpellier, France aut Mattoso Marta COPPE/Federal University of Rio de Janeiro, Rio de Janeiro, Brazil aut Journal of Grid Computing Springer Netherlands 13/4(2015-12-01), 457-493 1570-7873 13:4<457 2015 13 10723 https://doi.org/10.1007/s10723-015-9329-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10723-015-9329-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Liu Ji MSR-Inria Joint Centre, Inria and LIRMM and University of Montpellier, Montpellier, France aut NATIONALLICENCE 700 1- Pacitti Esther Inria and LIRMM, University of Montpellier, Montpellier, France aut NATIONALLICENCE 700 1- Valduriez Patrick MSR-Inria Joint Centre, Inria and LIRMM and University of Montpellier, Montpellier, France aut NATIONALLICENCE 700 1- Mattoso Marta COPPE/Federal University of Rio de Janeiro, Rio de Janeiro, Brazil aut NATIONALLICENCE 773 0- Journal of Grid Computing Springer Netherlands 13/4(2015-12-01), 457-493 1570-7873 13:4<457 2015 13 10723