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Journal Article
A Survey of Data-Intensive Scientific Workflow Management
2015
Overview
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.
Publisher
Springer Netherlands,Springer Nature B.V,Springer Verlag
