Artikel in Zeitschrift ART-2016-13

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.
CR-Klassif.E.0 (Data General)
E.1 (Data Structures)
H.1 (Models and Principles)
KeywordsData 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.

Volltext und
andere Links
Springer Link
KontaktPascal.Hirmer@ipvs.uni-stuttgart.de
Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Anwendersoftware
Projekt(e)SitOPT
Eingabedatum2. November 2016
   Publ. Informatik