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An Energy Efficient Virtual Machine Placement Algorithm Based on Graph Partitioning in Cloud Data Center

机译:基于云数据中心图分区的​​节能虚拟机放置算法

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Energy efficiency is a hot topic in the research of virtual machine placement (VMP). As the network equipment energy consumption problem has become increasingly prominent, many studies through resource aggregation to save energy, which can easily lead to resource competition and SLA violations. In this paper, we present a virtual machine placement algorithm based on graph partitioning (GPVMP) to achieve energy optimization. For the virtual machine (VM) group submitted by the user, we reconstruct the VM associated graph according to the traffic and load correlation between VMs, and partition the graph using the improved multilevel k-way partitioning algorithm. Combined with the data center topology, the two-layer mapping relationship of VMs and physical machines (PMs) is determined by extending PM clusters. The experimental results show that our proposed algorithm can guarantee better resource utilization, control SLA violation and offer a significant savings of energy compared with other related algorithms.
机译:能效是虚拟机放置(VMP)的研究中的热门话题。随着网络设备的能源消耗问题变得越来越突出,许多通过资源聚集来节省能源的研究,这很容易导致资源竞争和SLA违规。在本文中,我们介绍了一种基于曲线图分区(GPVMP)的虚拟机放置算法,以实现能量优化。对于由用户提交的虚拟机(VM)组,我们根据VM之间的流量和负载相关性重建VM关联图,并使用改进的多级k向划分算法分区图。结合数据中心拓扑,通过延伸PM簇来确定VM和物理机器(PMS)的双层映射关系。实验结果表明,与其他相关算法相比,我们所提出的算法可以保证更好的资源利用,控制SLA违规,并提供了大量节省能量。

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