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Towards Correct Cloud Resource Allocation in Business Processes
- Source :
- IEEE Transactions on Services Computing, IEEE Transactions on Services Computing, IEEE, 2017, 10 (1), pp.23-36. ⟨10.1109/TSC.2016.2594062⟩
- Publication Year :
- 2017
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2017.
-
Abstract
- International audience; Cloud environments are being increasingly used for deploying and executing business processes to provide a high level of performance with low operating cost. Nevertheless, due to the lack of an explicit and formal description of the resource perspective in the existing business processes, the correctness of Cloud resources management can not be verified. The aim of the present work is to offer a formal definition of the resource perspective in business processes as a step towards ensuring a correct and consistent Cloud resource allocation in business process modeling. Concretely, we propose a formalism based on the Event-B language for specifying Cloud resource allocation policies in business process models. This formal specification is used to formally validate the consistency of Cloud resource allocation for process modeling at design time, and to analyze and check its correctness according to user requirements and resource capabilities. In order to show its feasibility, our approach has been tested using a real use case study from an industrial partner.
- Subjects :
- Information Systems and Management
Process modeling
Computer Networks and Communications
business.industry
Business process
Computer science
Artifact-centric business process model
Distributed computing
Process mining
020206 networking & telecommunications
Cloud computing
[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]
02 engineering and technology
Business process modeling
Computer Science Applications
Business process management
Business Process Model and Notation
Hardware and Architecture
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
business
Software engineering
Subjects
Details
- ISSN :
- 19391374
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Services Computing
- Accession number :
- edsair.doi.dedup.....c178d09df02fa15731e2d2861ed7b455
- Full Text :
- https://doi.org/10.1109/tsc.2016.2594062