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Process-Mining-Based Workflow Model Fragmentation for Distributed Execution

机译:分布式执行的基于过程挖掘的工作流模型分段

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A complex workflow is often executed by geographically dispersed partners or different organizations. As a solution for dealing with the decentralized nature of workflow applications, a workflow can be fragmented into small pieces and scheduled to different servers for its execution. An important challenge in distributed workflows is to optimize the fragmentation and distribution to achieve efficiency with respect to time and server resources. To tackle this challenge, we propose the application of process mining to the fragmentation of a workflow for distributed execution. The workflow model discovered through process mining records the actual execution of a workflow and allows in-depth analysis of its temporal behavior. Based on examination of the model resulting from process mining, we demonstrate how to determine the minimum time to finish a workflow and how to partition the workflow in order to achieve efficient server usage.
机译:复杂的工作流程通常由地理位置分散的合作伙伴或不同的组织执行。作为处理工作流应用程序分散性的解决方案,可以将工作流分成多个小块,并安排到不同的服务器中执行。分布式工作流中的一个重要挑战是优化碎片和分布,以实现时间和服务器资源方面的效率。为了解决这一挑战,我们建议将流程挖掘应用于分散执行工作流的碎片。通过流程挖掘发现的工作流模型记录了工作流的实际执行情况,并允许对其时间行为进行深入分析。基于对过程挖掘产生的模型的检查,我们演示了如何确定完成工作流程的最短时间以及如何对工作流程进行分区,以实现有效的服务器使用。

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