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An Optimal Engine Component Placement Strategy for Cloud Workflow Service

机译:云工作流程服务的最佳发动机组件放置策略

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Workflows have been used to represent a variety of applications that involve coordinating a set of business services or scientific services, which are generally geographically distributed. With the development of cloud computing, a workflow engine can be deployed as a cloud service, responsible for executing customers' workflow instances. In a cloud workflow service, workflow engine components can be placed into different cloud regions. Thus, one challenging problem that arises is how to select the appropriate cloud regions to place the workflow engine components in order to efficiently execute a service workflow instance. Because this is a typical nondeterministic polynomial-time hard (NP-hard) problem, we propose a heuristic algorithm to select the regions where to place workflow engine components in an optimal and efficient way, with the objective of reducing the execution time of the service workflow instance. The experimental results prove that our proposed algorithm has higher performance than other approaches in terms of the solution quality and the running speed.
机译:工作流已被用于代表各种应用程序,这些应用程序涉及协调一系列商业服务或科学服务,这些服务通常在地理上分布。随着云计算的发展,可以将工作流引擎部署为云服务,负责执行客户的工作流程。在云工作流程服务中,可以将工作流引擎组件放入不同的云区域。因此,出现的一个具有挑战性的问题是如何选择适当的云区域以放置工作流引擎组件以便有效地执行服务工作流实例。因为这是一个典型的非季度多项式 - 时间硬(NP-Hard)问题,我们提出了一种启发式算法来选择以最佳和有效的方式将工作流引擎组件放置的区域,其目的是减少服务的执行时间工作流实例。实验结果证明,我们所提出的算法在溶液质量和运行速度方面具有比其他方法更高。

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