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An Optimal Heuristic Model for Greedy and Efficient Consolidation Process in Cloud Datacenters

机译:云数据中心贪婪和高效合并过程的最佳启发式模型

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Today, cloud computing has become an integrated solution for the entrepreneurs to deploy their business applications and to obtain the immense advantages of the cloud. Virtualization increased the cloud productivity and decreased the energy consumption by mapping the physical systems into logical virtual machines. Uneven distribution of load among the hosts may generate the host over subscription and under subscription issues, which impacts negatively on QoS management and energy consumption of cloud. Server consolidation is the convenient solution for handling the host underutilization issues. Although the former researches were proposed several advancements in consolidation, it is still suffering in selection of optimal threshold values and controls the aggressive migrations. This research work has proposed an optimal heuristic model for greedy and efficient consolidation process in cloud datacenters. Experimental results proven that the proposed consolidation model defined an optimal threshold value to save the energy and the greedy consolidation policy controlled the aggressive migrations better than the former consolidation models.
机译:今天,云计算已成为企业家部署其业务应用程序并获得云的巨大优势的集成解决方案。虚拟化通过将物理系统映射到逻辑虚拟机来增加云生产率并降低能量消耗。宿主之间的负荷分配不均匀可能会在订阅和订阅问题下产生主机,从而影响云的QoS管理和能耗的负面影响。服务器整合是处理主机未充分利用问题的方便解决方案。虽然前一项研究提出了统一的若干进步,但在选择最佳阈值并控制攻击性迁移时仍然遭受困扰。这项研究工作提出了云数据中心贪婪和有效的整合过程的最佳启发式模型。实验结果证明,该拟议的整合模型定义了拯救能源的最佳阈值,并将贪婪的合并政策控制了比以前的整合模型更好的侵略性迁移。

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