A decentralized execution model for inter-organizational workflows |
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Authors: | Vijayalakshmi Atluri Soon Ae Chun Ravi Mukkamala Pietro Mazzoleni |
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Affiliation: | (1) MS/IS Department, Rutgers University, Newark, NJ 07102, USA;(2) Information Systems, City University of New York, Staten Island, NY 10314, USA;(3) Computer Science Department, Old Dominion University, Norfolk, VA 23529, USA;(4) Dipartimento di Scienze dell’Informazione, University of Milan, via Comelico 39/41, 20135 Milano, Italy |
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Abstract: | Workflow Management Systems (WFMS) are often used to support the automated execution of business processes. In today’s networked
environment, it is not uncommon for organizations representing different business partners to collaborate for providing value-added
services and products. As such, workflows representing the business processes in this loosely-coupled, dynamic and ad hoc
coalition environment tend to span across the organizational boundaries. As a result, it is not viable to employ a single
centralized WFMS to control the execution of the inter-organizational workflow due to limited scalability, availability and performance. To this end, in this paper, we present a decentralized workflow model, where inter-task dependencies are enforced without requiring to have a centralized WFMS. In our model, a workflow is divided
into partitions called self-describing workflows, and handled by a light weight workflow management component, called the workflow stub, located at each organization. We present a performance study by considering different types of workflows with varying degrees
of parallelism. Our performance results indicate that decentralized workflow management indeed enjoys significant gain in
performance over its centralized counterpart in cases where there is less parallelism.
The work of V. Atluri is supported in part by the National Science Foundation under grant IIS-0306838. |
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Keywords: | Decentralized workflow execution Self-describing workflow Workflow partition Dependency split Workflow stub Evaluation of workflow execution |
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