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Workflow performance analysis and simulation based on multidimensional workflow net

机译:基于多维工作流网的工作流绩效分析与仿真

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Workflow model performance analysis plays an important role in the research of workflow techniques and efficient implementation of workflow management. Instances dwelling times (IDT) which consist of waiting times and handle times in a workflow model is a key performance analysis goal. In a workflow model the instances which act as customers and the resources which act as servers form a queuing network. Multidimensional workflow net (MWF-net) includes multiple timing workflow nets (TWF-nets) and the organization and resource information. This paper uses queuing theory and MWF-net to discuss mean value and probability distribution density function (PDDF) of IDT. It is assumed that the instances arrive with exponentially distributed inter-arrival times and the resources handle instances within exponentially distributed times or within constant times. First of all, the mean value and PDDF of IDT in each activity is calculated. Then the mean value and PDDF of IDT in each control structure of a workflow model is computed. According to the above results a method is proposed for computing the mean value and PDDF of IDT in a workflow model. Finally an example is used to show that the proposed method can be effectively utilized in practice.
机译:工作流模型性能分析在工作流技术研究和工作流管理的有效实施中起着重要作用。由工作流模型中的等待时间和处理时间组成的实例驻留时间(IDT)是关键的性能分析目标。在工作流模型中,充当客户的实例和充当服务器的资源形成排队网络。多维工作流网(MWF-net)包括多个计时工作流网(TWF-net)以及组织和资源信息。本文使用排队论和MWF网络讨论IDT的均值和概率分布密度函数(PDDF)。假定实例以指数分布的到达间隔时间到达,并且资源在指数分布的时间或恒定时间内处理实例。首先,计算每个活动中IDT的平均值和PDDF。然后,计算工作流模型的每个控制结构中IDT的平均值和PDDF。根据以上结果,提出了一种在工作流模型中计算IDT平均值和PDDF的方法。最后通过一个例子说明所提出的方法可以在实践中得到有效利用。

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