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HTSFR: Hierarchical Tabu Search with Fuzzy Reasoning for Optimal Resource Scheduling in Cloud Computing Environment

机译:HTSFR:具有模糊推理的分层禁忌搜索,用于云计算环境中的最佳资源调度

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The concept of virtual machines is critical to manage the scalable utilization of the resources in cloud computing. Hence the scheduling and balancing the assigned job loads to virtual machines is essential and exclusive need of the cloud computing environment, which is a critical research objective since, improving the service provision in cloud computing is not only through scheduling the individual resources to the target jobs, also the scheduling the virtual machines and balancing the load at virtual machines. In the context of this argument, a method called, Hierarchical Tabu Search with Fuzzy Reasoning (HTSFR) is proposed to escalate the optimality of resource scheduling and load balancing that deals the virtual machines as resources. The performance analysis was done on simulated environment established by using Cloud SIM. The results obtained from proposal were compared to other contemporary models, which evinced the significant performance advantage of the proposal on other contemporary models compared.
机译:虚拟机的概念对于管理云计算中资源的可扩展利用率至关重要。因此,调度和平衡分配给虚拟机的作业负载是云计算环境的基本需求,这是至关重要的研究目标,因为改善云计算中的服务提供不仅是通过将单个资源调度到目标作业来完成的。 ,还可以调度虚拟机并平衡虚拟机的负载。在此论点的背景下,提出了一种称为“具有模糊推理的分层禁忌搜索”(HTSFR)的方法,以提升将虚拟机视为资源的资源调度和负载平衡的最优性。在使用Cloud SIM建立的模拟环境中进行了性能分析。从提案中获得的结果与其他现代模型进行了比较,从而证明了该提案在其他现代模型上的显着性能优势。

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