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A decentralized execution model for inter-organizational workflows

机译:组织间工作流程的分散执行模型

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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 decentral- ized workflow management indeed enjoys significant gain in performance over its centralized counterpart in cases where there is less parallelism.
机译:工作流管理系统(WFMS)通常用于支持业务流程的自动化执行。在当今的网络环境中,代表不同业务伙伴的组织进行协作以提供增值服务和产品的情况并不少见。这样,在这种松耦合,动态且临时的联盟环境中,代表业务流程的工作流往往跨越组织边界。结果,由于有限的可伸缩性,可用性和性能,采用单个集中式WFMS来控制组织间工作流程的执行是不可行的。为此,在本文中,我们提出了一种分散的工作流模型,其中强制执行任务间依赖性,而无需使用集中式WFMS。在我们的模型中,工作流被划分为称为自我描述工作流的分区,并由位于每个组织的轻量级工作流管理组件(称为工作流存根)进行处理。我们通过考虑具有不同并行度的不同类型的工作流来进行性能研究。我们的性能结果表明,在并行度较低的情况下,分散式工作流管理的确比集中式工作流管理具有显着的性能提升。

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