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Two-level Dynamic Workflow Orchestration in the INDIGO DataCloud for Large-scale, Climate Change Data Analytics Experiments
Copyright policy )Two-level Dynamic Workflow Orchestration in the INDIGO DataCloud for Large-scale, Climate Change Data Analytics Experiments
AbstractIn this paper we present the approach proposed by EU H2020 INDIGO-DataCloud project to orchestrate dynamic workflows over a cloud environment. The main focus of the project is on the development of open source Platform as a Service solutions targeted at scientific communities, deployable on multiple hardware platforms, and provisioned over hybrid e-Infrastructures. The project is addressing many challenging gaps in current cloud solutions, responding to specific requirements coming from scientific communities including Life Sciences, Physical Sciences and Astronomy, Social Sciences and Humanities, and Environmental Sciences. We are presenting the ongoing work on implementing the whole software chain on the Infrastructure as a Service, PaaS and Software as a Service layers, focusing on the scenarios involving scientific workflows and big data analytics frameworks. INDIGO module for Kepler worflow system has been introduced along with the INDIGO underlying services exploited by the workflow components. A climate change data analytics experiment use case regarding the precipitation trend analysis on CMIP5 data is described, that makes use of Kepler and big data analytics services.
Microsoft Academic Graph classification: Computer science Big data Cloud computing Orchestration (computing) business.industry Software as a service Provisioning Data science Workflow Analytics Data analysis business
FutureGateway, INDIGO, cloud, Climate change, PaaS, General Environmental Science, Ophidia, General Earth and Planetary Sciences, Kepler, Cloud
FutureGateway, INDIGO, cloud, Climate change, PaaS, General Environmental Science, Ophidia, General Earth and Planetary Sciences, Kepler, Cloud
Microsoft Academic Graph classification: Computer science Big data Cloud computing Orchestration (computing) business.industry Software as a service Provisioning Data science Workflow Analytics Data analysis business
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[1] CMIP5. http://cmip-pcmdi.llnl.gov/cmip5/. Accessed: February, 04. 2016.
[2] Climate Data Operators. https://code.zmaw.de/projects/cdo. Accessed: February, 04. 2016.
[3] EGI website. http://www.egi.eu/. Accessed: February, 04. 2016.
[4] EUDAT website. http://www.eudat.eu/. Accessed: February, 04. 2016.
[5] Helix-Nebula website. http://www.helix-nebula.eu/. Accessed: February, 04. 2016.
[6] INDIGO-DataCloud website. https://www.indigo-datacloud.eu/. Accessed: February, 04. 2016.
[7] The JSAGA website. http://grid.in2p3.fr/jsaga. Accessed: February, 04. 2016.
[8] The Liferay portal framework. http://www.liferay.com. Accessed: February, 04. 2016.
[9] The SAGA OGF Standard Specification. http://www.ogf.org/documents/GFD.90.pdf. Accessed: February, 04. 2016.
[10] V. et al Ardizzone. A european framework to build science gateways: Architecture and use cases. In Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery, TG '11, pages 43:1- 43:2, 2011.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).4 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).4 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!
- Lawrence Berkeley National Laboratory United States
- Istituto Nazionale di Fisica Nucleare
- ISTITUTO NAZIONALE DI FISICA NUCLEARE Italy
- National Institute for Nuclear Physics Italy
- University of Salento Italy
- Lawrence Livermore National Laboratory United States
- ISTITUTO NAZIONALE DI FISICA NUCLEARE
- FONDAZIONE CENTRO EURO-MEDITERRANEOSUI CAMBIAMENTI CLIMATICI Italy
AbstractIn this paper we present the approach proposed by EU H2020 INDIGO-DataCloud project to orchestrate dynamic workflows over a cloud environment. The main focus of the project is on the development of open source Platform as a Service solutions targeted at scientific communities, deployable on multiple hardware platforms, and provisioned over hybrid e-Infrastructures. The project is addressing many challenging gaps in current cloud solutions, responding to specific requirements coming from scientific communities including Life Sciences, Physical Sciences and Astronomy, Social Sciences and Humanities, and Environmental Sciences. We are presenting the ongoing work on implementing the whole software chain on the Infrastructure as a Service, PaaS and Software as a Service layers, focusing on the scenarios involving scientific workflows and big data analytics frameworks. INDIGO module for Kepler worflow system has been introduced along with the INDIGO underlying services exploited by the workflow components. A climate change data analytics experiment use case regarding the precipitation trend analysis on CMIP5 data is described, that makes use of Kepler and big data analytics services.