Characterization of scientific workflows
By S. Bharathi, Ann L. Chervenak, Ewa Deelman, Gaurang Mehta, Mei-Hui Su, Karan Vahi. 2008 Third Workshop on Workflows in Support of Large-Scale Science, 2008
631 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems and Management
View Paper: https://www.semanticscholar.org/paper/1324f1d5b20f08cac775f10089a788767c56d5a9
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In Computer Networks and Communications
In Information Systems and Management
Citations in the corpus
- Evolutionary Multi-Objective Workflow Scheduling in Cloud (2016, neutral): “Pegasus project has published the workflow of a number of real-world applications including Montage, CyberShake, Epigenomics, LIGO Inspiral Analysis and 9 SIPHT [36], [37].”
- Cost- and deadline-constrained provisioning for scientific workflow ensembles in IaaS clouds (2012, methodology): “Our experience suggests that such assumption is often reasonable, since we can obtain workflow performance characteristics from preliminary runs [22], [25], [26].”
- Cost optimized provisioning of elastic resources for application workflows (2011, background): “We assume that the execution time of individual tasks are given by users [19].”
- Cloud auto-scaling with deadline and budget constraints (2010, methodology): “Case 3) Montage [24][25] was created by the NASA/IPAC Infrared Science Archive as an open source toolkit that can be used to generate custom mosaics of the sky using input images in the Flexible Image Transport System (FITS) format.”