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Resource and Task Clustering based Scheduling Algorithm for Workflow Applications in Cloud Computing Environment

机译:基于资源和任务群集的云计算环境中工作流应用的调度算法

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Cloud computing consists of distributed resources and used to provide services to the applications which require huge computation power such as scientific, mathematical, weather forecasting, and biomedical applications. These applications are considered as workflow applications containing many numbers of dependent tasks. The scheduling of these dependent tasks on distributed resources is a critical problem in cloud computing. In this paper, we present a scheduling algorithm that considers clustering of resources and tasks for workflow applications in the cloud computing environment. The given algorithm is an enhancement toHySARC algorithm. Like HySARC, the proposed algorithm first forms clusters of resources and tasks and then applies list scheduling techniques on each of the clusters to schedule tasks. We have estimated and compared the performance of the proposed algorithm with HySARC algorithm on the parameters like clustering time, and makespan, and found that the proposed algorithm performed better than the compared algorithm.
机译:云计算包括分布式资源,并用于为需要巨大计算能力的应用提供服务,如科学,数学,天气预报和生物医学应用。这些应用程序被视为包含许多依赖任务的工作流应用程序。分布式资源上的这些依赖任务的调度是云计算中的一个关键问题。在本文中,我们介绍了一种调度算法,其考虑云计算环境中的工作流应用程序的资源和任务的群集。给定的算法是增强次幂术算法。与hysarc一样,所提出的算法首先形成资源和任务的集群,然后在每个群集中应用列表调度技术以调度任务。我们估计并与Hysarc算法对聚类时间和MakEspan等参数进行了比较了所提出的算法的性能,发现所提出的算法比比较算法更好。

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