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Paving the Way for Energy Efficient Cloud Data Centers: A Type-Aware Virtual Machine Placement Strategy

机译:为节能型云数据中心铺平道路:一种类型感知型虚拟机放置策略

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The rapid revolution of cloud computing model is accompanied by huge amounts of energy consumed by the cloud data centers. So, enhancing the energy efficiency of those data centers has become a major challenge. This paper tackles the problem of enhancing the energy consumption of cloud data centers by proposing a novel virtual machine placement strategy. The proposed strategy suits both static and dynamic placement process. It aims to better utilize the involved physical machines which host the virtual machines. As different types of jobs do not intensively use the compute and/or non-compute resources in the hosted physical machine, virtual machines allocated to the jobs of different types are placed on the same physical machine where possible. The paper presents a mathematical formulation of the virtual machine placement process based on the Multiple Choice Knapsack Problem which is a generalization of the classical Knapsack Problem. The performance evaluation of the proposed strategy shows that it can enhance the energy efficiency of the cloud data centers by trying to minimize the number of the involved physical machines which host the virtual machines, and by optimally utilizing the involved physical machines.
机译:云计算模型的快速变革伴随着云数据中心消耗的大量能源。因此,提高这些数据中心的能源效率已成为一项重大挑战。本文通过提出一种新颖的虚拟机放置策略来解决增加云数据中心能耗的问题。所提出的策略适合静态和动态放置过程。它旨在更好地利用托管虚拟机的相关物理机。由于不同类型的作业不会大量使用托管物理机中的计算和/或非计算资源,因此,分配给不同类型作业的虚拟机将尽可能放置在同一物理机上。本文提出了基于多项选择背包问题的虚拟机放置过程的数学公式,该问题是经典背包问题的推广。所提出策略的性能评估表明,通过尝试最小化托管虚拟机的所涉及物理机的数量以及最佳地利用所涉及的物理机,可以提高云数据中心的能源效率。

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