Bibliography | Hirmer, Pascal; Mitschang, Bernhard: TOSCA4Mashups: enhanced method for on-demand data mashup provisioning. In: Computer Science - Research and Development. University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology. pp. 1-10, english. Springer Berlin Heidelberg, October 31, 2016. DOI: 10.1007/s00450-016-0330-7. Article in Journal.
|
CR-Schema | E.0 (Data General) E.1 (Data Structures) H.1 (Models and Principles)
|
Keywords | Data Mashups; TOSCA; Provisioning; Cloud Computing |
Abstract | 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.
|
Full text and other links | Springer Link
|
Contact | Pascal.Hirmer@ipvs.uni-stuttgart.de |
Department(s) | University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems
|
Project(s) | SitOPT
|
Entry date | November 2, 2016 |
---|