On-demand task assignment strategies for workflow-based applications in cloud manufacturing

Mingwei Wang*, Jingtao Zhou, Shikai Jing

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

Large and complex cloud manufacturing applications relies on co-operation between self-governed manufacturing clouds. Since each manufacturing cloud has its own capacity, the tasks defined in the workflow are allocated to distributed clouds to achieve a predetermined goal. In this paper, a study on on-demand task assignment strategy for workflow-based cloud manufacturing applications is presented, which aims to build a flexible workflow implementation mechanism. The proposed strategy assigns the tasks through the process of business process model instantiation. Four important influencing factors during task assigning process and their measuring methods are given in detail. To raise the degree of automation in assigning, matching methods between task requirements and the workflow engine are given for each factor. Simulation experiments validate the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)308-313
Number of pages6
JournalJisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics
Volume24
Issue number3
Publication statusPublished - Mar 2012

Keywords

  • Capacity matching
  • Cloud manufacturing
  • Task assignment
  • Workflow engine

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