Stochastic modeling and quality evaluation of workflow systems based on QWF-nets
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Stochastic modeling and quality evaluation of workflow systems based on QWF-nets

Presented By:
Xia Yunni , Wang Han Pin, Yuan Chong Yi, and Chunxiang Xu School of Electronics Engineering and Computer Science Peking University, China

Abstract. Quality (QOS) prediction is one of the most important re- search topics of workfow management system. The management of QOS metrics directly impacts the success of organizations participating in workfow-based applications. Therefore, when services or products are created or managed using workfows or Web processes, the underlying workfow engine must accept the speci¯cations and be able to estimate, monitor, and control the QOS rendered to customers. In this paper, we propose the SWQ approach to evaluate QOS of workfow systems based on QWF-net, which extends traditional WF-net by associating tasks with exponential response time and exponential TTF (time-to-failure). The comparison between simulative results and SWQ results in the example study indicates that the SWQ approach achieves satisfactory accuracy. The paper concludes with a comparison between the SWQ approach and other related work.
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