Bibliograph. Daten | Hirmer, Pascal; Mitschang, Bernhard: TOSCA4Mashups: enhanced method for on-demand data mashup provisioning. In: Computer Science - Research and Development. Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik. S. 1-10, englisch. Springer Berlin Heidelberg, 31. Oktober 2016. DOI: 10.1007/s00450-016-0330-7. Artikel in Zeitschrift.
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CR-Klassif. | E.0 (Data General) E.1 (Data Structures) H.1 (Models and Principles)
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Keywords | Data Mashups; TOSCA; Provisioning; Cloud Computing |
Kurzfassung | Nowadays, the amount of data increases tremendously. Extracting information and generating knowledge from this data is a great challenge. To cope with this issue – oftentimes referred to as big data problem – we need effective means for efficient data integration, data processing, and data analysis. To enable flexible, explorative and ad-hoc data processing, several data mashup approaches and tools have been developed in the past. One of these tools is FlexMash – a data mashup tool developed at the University of Stuttgart. By offering domain-specific graphical modeling as well as a pattern-based execution, FlexMash enables usage by a wide range of users, both domain experts and technical experts. The core idea of FlexMash is a flexible execution of data mashups using different, user-requirement-dependent execution components. In this paper, we present a new approach for on-demand, automated provisioning of these components in a cloud computing environment using the Topology and Orchestration Specification for Cloud Applications. This enables many advantages for mashup execution such as scalability, availability and cost savings.
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Volltext und andere Links | Springer Link
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Kontakt | Pascal.Hirmer@ipvs.uni-stuttgart.de |
Abteilung(en) | Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Anwendersoftware
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Projekt(e) | SitOPT
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Eingabedatum | 2. November 2016 |
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