Analyzing Degree of Parallelism for Concurrent Timed Workflow Processes With Shared Resources

• Published in: IEEE transactions on engineering management Vol. 64; no. 1; pp. 42 - 56
• Main Authors: Du, Yanhua, Wang, Li, Li, Xitong
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-02-2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Analytical models; Business; Business machines; Business process management; Computational modeling; degree of parallelism; Multitasking; Parallel processing; Petri net (<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX"> PN</tex-math> </inline-formula> </named-content>); Process management; Process planning; Processor scheduling; Servers; Studies; timed workflow net (<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX"> TWF-Net </tex-math> </inline-formula> </named-content>); Uncertainty; Virtual environments; Workflow; workflow management; Workflow software
• ISSN: 0018-9391; 1558-0040
• DOI: 10.1109/TEM.2016.2621726

Degree of parallelism is an important factor in workflow process management, because it is useful to accurately estimate the server costs and schedule severs in workflow processes. However, existing methods that are developed to compute degree of parallelism neglect to consider activities with uncertain execution time. In addition, these methods are limited in dealing with the situation where activities in multiple concurrent workflow processes use shared resources. To address the limitations, we propose a new approach to analyzing degree of parallelism for concurrent workflow processes with shared resources. Superior over the existing methods, our approach can compute degree of parallelism for multiple concurrent workflow processes that have activities with uncertain execution time and shared resources. Expectation degree of parallelism is useful to estimate the server costs of the workflow processes, and maximum degree of parallelism can guide managers to allocate severs or virtual machines based on the business requirement. We demonstrate the application of the approach and evaluate the effectiveness in a real-world business scenario.