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Toward an End-to-End Framework for Modeling, Monitoring and Anomaly Detection for Scientific Workflows.

, , , , , , , , , , , , , , , , and . IPDPS Workshops, page 1370-1379. IEEE Computer Society, (2016)

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Grids and Clouds: Making Workflow Applications Work in Heterogeneous Distributed Environments.. Int. J. High Perform. Comput. Appl., 24 (3): 284-298 (2010)A provisioning model and its comparison with best-effort for performance-cost optimization in grids., , and . HPDC, page 117-126. ACM, (2007)Artemis: Integrating Scientific Data on the Grid., , , and . AAAI, page 892-899. AAAI Press / The MIT Press, (2004)Wrangler: virtual cluster provisioning for the cloud., and . HPDC, page 277-278. ACM, (2011)Exploration of Workflow Management Systems Emerging Features from Users Perspectives., , , , , , and . IEEE BigData, page 4537-4544. IEEE, (2019)Accelerating Scientific Workflows on HPC Platforms with In Situ Processing., , , , , , and . CCGRID, page 1-10. IEEE, (2022)Grid-Based Galaxy Morphology Analysis for the National Virtual Observatory., , , , , , , , , and 8 other author(s). SC, page 47. ACM, (2003)Cost- and deadline-constrained provisioning for scientific workflow ensembles in IaaS clouds., , , and . SC, page 22. IEEE/ACM, (2012)Science automation in practice: Performance data farming in workflows., , , , , , and . ETFA, page 1-4. IEEE, (2016)Training Classifiers to Identify TCP Signatures in Scientific Workflows., , , , and . INDIS@SC, page 61-68. IEEE, (2019)