Precise Quantitative Analysis of Probabilistic Business Process Model and Notation Workflows

Publication: Research - peer-reviewJournal article – Annual report year: 2013

View graph of relations

We present a framework for modeling and analysis of real-world business workflows. We present a formalized core subset of the business process modeling and notation (BPMN) and then proceed to extend this language with probabilistic nondeterministic branching and general-purpose reward annotations. We present an algorithm for the translation of such models into Markov decision processes (MDP) expressed in the syntax of the PRISM model checker. This enables precise quantitative analysis of business processes for the following properties: transient and steady-state probabilities, the timing, occurrence and ordering of events, reward-based properties, and best- and worst- case scenarios. We develop a simple example of medical workflow and demonstrate the utility of this analysis in accurate provisioning of drug stocks. Finally, we suggest a path to building upon these techniques to cover the entire BPMN language, allow for more complex annotations and ultimately to automatically synthesize workflows by composing predefined subprocesses, in order to achieve a configuration that is optimal for parameters of interest.
Original languageEnglish
JournalJournal of Computing and Information Science in Engineering
Volume13
Issue number1
Pages (from-to)011007
Number of pages9
ISSN1530-9827
DOIs
StatePublished - 2013
CitationsWeb of Science® Times Cited: 1

    Keywords

  • BPMN, Stochastic BPMN, Stochastic model checking, PRISM, Quantitative workflow analysis
Download as:
Download as PDF
Select render style:
APAAuthorCBE/CSEHarvardMLAStandardVancouverShortLong
PDF
Download as HTML
Select render style:
APAAuthorCBE/CSEHarvardMLAStandardVancouverShortLong
HTML
Download as Word
Select render style:
APAAuthorCBE/CSEHarvardMLAStandardVancouverShortLong
Word

ID: 53802785