Artikel in Zeitschrift ART-2016-13

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.
CR-Klassif.E.0 (Data General)
E.1 (Data Structures)
H.1 (Models and Principles)
KeywordsData Mashups; TOSCA; Provisioning; Cloud Computing

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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Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Anwendersoftware
Eingabedatum2. November 2016
   Publ. Abteilung   Publ. Institut   Publ. Informatik