Artikel in Tagungsband INPROC-2017-56

Zimmermann, Michael; Breitenbücher, Uwe; Falkenthal, Michael; Leymann, Frank; Saatkamp, Karoline: Standards-based Function Shipping - How to use TOSCA for Shipping and Executing Data Analytics Software in Remote Manufacturing Environments.
In: Proceedings of the 2017 IEEE 21st International Enterprise Distributed Object Computing Conference (EDOC 2017).
Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik.
S. 50-60, englisch.
IEEE Computer Society, 10. Oktober 2017.
DOI: 10.1109/EDOC.2017.16.
Artikel in Tagungsband (Konferenz-Beitrag).
CR-Klassif.D.2.13 (Software Engineering Reusable Software)

The increasing amount of gathered sensor data in Industry 4.0 allows comprehensive data analysis software that creates value-adding opportunities. As companies often cannot implement such software by themselves and as they typically don't want to give their data to external scientists, they commission them to build the required software in order to execute it locally. However, installing, configuring, and running complex third party software on another company's infrastructure and linking them to local data sources challenges the responsible administrators due to an immense technical complexity. Moreover, standards-based approaches for automation are missing. In this paper, we present three TOSCA-based deployment modelling approaches for function shipping that enable modelling data analysis software in a way that enables (i) its automated deployment and execution in a remote, foreign IT infrastructure including (ii) the wiring with the data sources that need to be processed in this environment. We validate the practical feasibility of the presented modelling approaches by a case study from the domain of manufacturing, which is based on the open-source TOSCA ecosystem OpenTOSCA, which provides a modelling tool, a runtime, as well as a self-service portal for TOSCA.

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Abteilung(en)Universität Stuttgart, Institut für Architektur von Anwendungssystemen
Eingabedatum9. November 2017
   Publ. Institut   Publ. Informatik