Process-Mining-Based Workflow Model Fragmentation for Distributed Execution

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

40 Scopus Citations
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Author(s)

  • Sherry X. Sun
  • Qingtian Zeng
  • Huaiqing Wang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)294-310
Journal / PublicationIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans.
Volume41
Issue number2
Online published11 Oct 2010
Publication statusPublished - Mar 2011

Abstract

A complex workflow is often executed by geographically dispersed partners or different organizations. As a solution for dealing with the decentralized nature of workflow applications, a workflow can be fragmented into small pieces and scheduled to different servers for its execution. An important challenge in distributed workflows is to optimize the fragmentation and distribution to achieve efficiency with respect to time and server resources. To tackle this challenge, we propose the application of process mining to the fragmentation of a workflow for distributed execution. The workflow model discovered through process mining records the actual execution of a workflow and allows in-depth analysis of its temporal behavior. Based on examination of the model resulting from process mining, we demonstrate how to determine the minimum time to finish a workflow and how to partition the workflow in order to achieve efficient server usage.

Research Area(s)

  • Distributed workflow, Petri net, process mining, task assignment, workflow management, workflow model fragmentation