Kepler + CometCloud: Dynamic Scientific Workflow Execution on Federated Cloud Resources

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dc.contributor.authorWang, Jianwu
dc.contributor.authorAbdelBaky, Moustafa
dc.contributor.authorDiaz-Montes, Javier
dc.contributor.authorPurawat, Shweta
dc.contributor.authorParashar, Manish
dc.contributor.authorAltintas, Ilkay
dc.date.accessioned2024-02-12T16:25:52Z
dc.date.available2024-02-12T16:25:52Z
dc.date.issued2016-06-01
dc.descriptionInternational Conference on Computational Science 2016, ICCS 2016, 6-8 June 2016, San Diego, California, USA
dc.description.abstractThe widespread availability and variety of cloud offerings and their associated access models has drastically grown over the past few years. It is now common for users to have access to multiple infrastructures (e.g., campus clusters, cloud resources), however, deploying complex application workflows on top of these resources remains a challenge. In this paper we propose an approach that allows users to build and run scientific workflows on top of a federation of multiple clouds and traditional resources (e.g., clusters). We achieve this by integrating the Kepler scientific workflow platform with the CometCloud framework. This allows us to: 1) dynamically and programmatically provision and aggregate resources, 2) easily compose complex workflows, and 3) dynamically schedule and execute these workflows based on provenance and overall objectives on the resulting federation of resources. We demonstrate our approach and evaluate its capabilities by running a bioinformatics workflow on top of a federation composed of a campus cluster and two clouds.
dc.description.sponsorshipThe research presented in this work is supported in part by National Science Foundation (NSF) via grants numbers ACI 1339036, ACI 1310283, ACI 1441376. This project used resources from Chameleon supported by NSF OCI-1419152. The research at UMBC was supported by a startup fund. The research at Rutgers was conducted as part of the Rutgers Discovery Informatics Institute (RDI2)
dc.description.urihttps://www.sciencedirect.com/science/article/pii/S1877050916308389
dc.format.extent12 pages
dc.genreconference papers and proceedings
dc.identifier.citationWang, Jianwu, Moustafa AbdelBaky, Javier Diaz-Montes, Shweta Purawat, Manish Parashar, and Ilkay Altintas. “Kepler + CometCloud: Dynamic Scientific Workflow Execution on Federated Cloud Resources.” Procedia Computer Science, International Conference on Computational Science 2016, ICCS 2016, 6-8 June 2016, San Diego, California, USA, 80 (January 1, 2016): 700–711. https://doi.org/10.1016/j.procs.2016.05.363.
dc.identifier.urihttps://doi.org/10.1016/j.procs.2016.05.363
dc.identifier.urihttp://hdl.handle.net/11603/31597
dc.language.isoen_US
dc.publisherElsevier
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Center for Accelerated Real Time Analysis
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department
dc.relation.ispartofUMBC Data Science
dc.relation.ispartofUMBC Joint Center for Earth Systems Technology (JCET)
dc.relation.ispartofUMBC Center for Real-time Distributed Sensing and Autonomy
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rightsAttribution-NonCommercial-NoDerivs 4.0 International (CC BY-NC-ND 4.0 DEED) en
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectUMBC Big Data Analytics Lab
dc.titleKepler + CometCloud: Dynamic Scientific Workflow Execution on Federated Cloud Resources
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0002-9933-1170

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