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Lookup NU author(s): Dr Jacek CalaORCiD, Eyad Marei, Dr Yaobo Xu, Professor Paolo MissierORCiD
This is the final published version of a report that has been published in its final definitive form by School of Computing Science, University of Newcastle upon Tyne, 2016.
For re-use rights please refer to the publisher's terms and conditions.
Dataflow-style workflows offer a simple, high-level programming model for flexible prototyping of scientific applications as an attractive alternative to low-level scripting. At the same time, workflow management systems (WfMS) may support data parallelism over big datasets by providing scalable, distributed deployment and execution of the workflow over a cloud infrastructure. In theory, the combination of these properties makes workflows a natural choice for implementing Big Data processing pipelines, common for instance in bioinformatics. In practice, however, correct workflow design for parallel Big Data problems can be complex and very time-consuming.
Author(s): Cala J, Marei E, Xu Y, Takeda K, Missier P
Publication type: Report
Publication status: Published
Series Title: School of Computing Science Technical Report Series
Year: 2016
Pages: 25
Print publication date: 01/01/2016
Acceptance date: 01/01/2016
Report Number: 1491
Institution: School of Computing Science, University of Newcastle upon Tyne
Place Published: Newcastle upon Tyne
