Korte, Fabian

[["dc.bibliographiccitation.journal","Software and Systems Modeling"],["dc.contributor.author","Zalila, Faiez"],["dc.contributor.author","Korte, Fabian"],["dc.contributor.author","Erbel, Johannes"],["dc.contributor.author","Challita, Stéphanie"],["dc.contributor.author","Grabowski, Jens"],["dc.contributor.author","Merle, Philippe"],["dc.date.accessioned","2022-11-01T10:17:37Z"],["dc.date.available","2022-11-01T10:17:37Z"],["dc.date.issued","2022"],["dc.identifier.doi","10.1007/s10270-022-01024-x"],["dc.identifier.pii","1024"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/116860"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-605"],["dc.relation.eissn","1619-1374"],["dc.relation.issn","1619-1366"],["dc.rights.uri","https://www.springer.com/tdm"],["dc.title","MoDMaCAO: a model-driven framework for the design, validation and configuration management of cloud applications based on OCCI"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","517"],["dc.bibliographiccitation.lastpage","525"],["dc.contributor.author","Grabowski, Jens"],["dc.contributor.author","Korte, Fabian"],["dc.contributor.author","Erbel, Johannes Martin"],["dc.date.accessioned","2019-07-29T13:33:11Z"],["dc.date.available","2019-07-29T13:33:11Z"],["dc.date.issued","2018"],["dc.description.abstract","To tackle the cloud provider lock-in, multiple standards have emerged to enable the uniform management of cloud resources across different providers. One of them is the Open Cloud Computing Interface (OCCI) which defines, in addition to a REST API, a metamodel that enables the modelling of cloud resources on different service layers. Even though the standard defines how to manage single cloud resources, no process exists that allows for the automated provisioning of full application topologies and their adaptation at runtime. Therefore, we propose a model-based approach to adapt running cloud application infrastructures, allowing a management on a high abstraction level. Hereby, we check the differences between the runtime and target state of the topology using a model comparison, matching their resources. Based on this match, we mark each resource indicating required management calls that are systematically executed by an adaptation engine. To show the feasibility of our approach, we"],["dc.identifier.doi","10.5220/0006774405170525"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/62147"],["dc.language.iso","en"],["dc.relation.conference","8th International Conference on Cloud Computing and Services Science"],["dc.relation.eventend","2018-03-21"],["dc.relation.eventlocation","Funchal, Madeira, Portugal"],["dc.relation.eventstart","2018-03-19"],["dc.relation.isbn","978-989-758-295-0"],["dc.relation.ispartof","CLOSER 2018: Proceedings of the 8th International Conference on Cloud Computing and Services Science"],["dc.title","Comparison and Runtime Adaptation of Cloud Application Topologies based on OCCI"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Software and Systems Modeling"],["dc.contributor.author","Challita, Stéphanie"],["dc.contributor.author","Korte, Fabian"],["dc.contributor.author","Erbel, Johannes"],["dc.contributor.author","Zalila, Faiez"],["dc.contributor.author","Grabowski, Jens"],["dc.contributor.author","Merle, Philippe"],["dc.date.accessioned","2021-04-14T08:29:10Z"],["dc.date.available","2021-04-14T08:29:10Z"],["dc.date.issued","2021"],["dc.identifier.doi","10.1007/s10270-021-00869-y"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82817"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","1619-1374"],["dc.relation.issn","1619-1366"],["dc.title","Model-based cloud resource management with TOSCA and OCCI"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","176"],["dc.bibliographiccitation.lastpage","192"],["dc.contributor.author","Korte, Fabian"],["dc.contributor.author","Bufe, Alexander"],["dc.contributor.author","Kohler, Christian W."],["dc.contributor.author","Brenner, Gunther"],["dc.contributor.author","Grabowski, Jens"],["dc.contributor.author","Wieder, Philipp"],["dc.contributor.author","Schöbel, A."],["dc.contributor.editor","Baum, M."],["dc.contributor.editor","Brenner, G."],["dc.contributor.editor","Grabowski, J."],["dc.contributor.editor","Hanschke, T."],["dc.contributor.editor","Hartmann, S."],["dc.date.accessioned","2019-07-30T12:36:11Z"],["dc.date.available","2019-07-30T12:36:11Z"],["dc.date.issued","2018"],["dc.description.abstract","Many simulations require large amounts of computing power to be executed. Traditionally, the computing power is provided by large high performance computing clusters that are solely built for this purpose. However, modern data centers do not only provide access to these high performance computing systems, but also offer other types of computing resources e.g., cloud systems, grid systems, or access to specialized computing resources, such as clusters equipped with accelerator hardware. Hence, the researcher is confronted with the choice of picking a suitable computing resource type for his simulation and acquiring the knowledge on how to access and manage his simulation on the resource type of choice. This is a time consuming and cumbersome process and could greatly benefit from supportive tooling. In this paper, we introduce a framework that allows to describe the simulation application in a resource-independent manner. It furthermore helps to select a suitable resource type according to the requirements of the simulation application and to automatically provision the required computing resources. We demonstrate the feasibility of the approach by providing a case study from the area of fluid mechanics."],["dc.identifier.doi","10.1007/978-3-319-96271-9_11"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/62197"],["dc.language.iso","en"],["dc.relation.isbn","978-3-319-96270-2"],["dc.relation.isbn","978-3-319-96271-9"],["dc.relation.ispartof","Simulation Science. SimScience 2017."],["dc.relation.orgunit","Gesellschaft für wissenschaftliche Datenverarbeitung"],["dc.title","Transparent Model-Driven Provisioning of Computing Resources for Numerically Intensive Simulations"],["dc.type","book_chapter"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]