Kepler + CometCloud: Dynamic Scientific Workflow Execution on Federated Cloud Resources
dc.contributor.author | Wang, Jianwu | |
dc.contributor.author | AbdelBaky, Moustafa | |
dc.contributor.author | Diaz-Montes, Javier | |
dc.contributor.author | Purawat, Shweta | |
dc.contributor.author | Parashar, Manish | |
dc.contributor.author | Altintas, Ilkay | |
dc.date.accessioned | 2024-02-12T16:25:52Z | |
dc.date.available | 2024-02-12T16:25:52Z | |
dc.date.issued | 2016-06-01 | |
dc.description | International Conference on Computational Science 2016, ICCS 2016, 6-8 June 2016, San Diego, California, USA | |
dc.description.abstract | The 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.sponsorship | The 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.uri | https://www.sciencedirect.com/science/article/pii/S1877050916308389 | |
dc.format.extent | 12 pages | |
dc.genre | conference papers and proceedings | |
dc.identifier.citation | Wang, 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.uri | https://doi.org/10.1016/j.procs.2016.05.363 | |
dc.identifier.uri | http://hdl.handle.net/11603/31597 | |
dc.language.iso | en_US | |
dc.publisher | Elsevier | |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC Information Systems Department Collection | |
dc.relation.ispartof | UMBC Faculty Collection | |
dc.relation.ispartof | UMBC Center for Accelerated Real Time Analysis | |
dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department | |
dc.relation.ispartof | UMBC Data Science | |
dc.relation.ispartof | UMBC Joint Center for Earth Systems Technology (JCET) | |
dc.relation.ispartof | UMBC Center for Real-time Distributed Sensing and Autonomy | |
dc.rights | This 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.rights | Attribution-NonCommercial-NoDerivs 4.0 International (CC BY-NC-ND 4.0 DEED) | en |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject | UMBC Big Data Analytics Lab | |
dc.title | Kepler + CometCloud: Dynamic Scientific Workflow Execution on Federated Cloud Resources | |
dc.type | Text | |
dcterms.creator | https://orcid.org/0000-0002-9933-1170 |