Data-intensive workflow management for clouds and data-intensive and scalable computing environments - Oliveira, Daniel de; Liu, Ji; Pacitti, Esther (Morgan & Claypool Publishers, 2019)
Workflows may be defined as abstractions used to model the coherent flow of activities in the context of an in silico scientific experiment. They are employed in many domains of science such as bioinformatics, astronomy, and engineering. Such workflows usually present a considerable number of activities and activations (i.e., tasks associated with activities) and may need a long time for execution. Due to the continuous need to store and process data efficiently (making them data-intensive workflows), high-performance computing environments allied to parallelization techniques are used to run these workflows. At the beginning of the 2010s, cloud technologies emerged as a promising environment to run scientific workflows. By using clouds, scientists have expanded beyond single parallel computers to hundreds or even thousands of virtual machines.
Part of: Synthesis digital library of engineering and computer science
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Keywords: Cloud computing; Database management; Datenverwaltung; Cloud Computing; Prozessmanagement; Big Data