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A System Architecture for Running Big Data Workflows in the Cloud
2014
2014 IEEE International Conference on Services Computing
Scientific workflows have become an important paradigm for domain scientists to formalize and structure complex data-intensive scientific processes. The everincreasing volumes of scientific data motivate researchers to extend scientific workflow management systems (SWFMSs) to utilize the power of Cloud computing to perform big data analyses. Unlike workflows run in traditional on-premise environments such as stand-alone workstations or grids, Cloud workflows rely on dynamically provisioned
doi:10.1109/scc.2014.16
dblp:conf/IEEEscc/KashlevL14
fatcat:4mmgfb7lafdfrovnpmvtgp7gfi