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

机译:云数据中心基于图划分的高效节能虚拟机布局算法

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摘要

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:能源效率是虚拟机放置(VMP)研究的热门话题。随着网络设备能耗问题日益突出,许多研究通过资源聚合来节约能源,这很容易导致资源竞争和违反SLA的行为。在本文中,我们提出了一种基于图分区(GPVMP)的虚拟机放置算法,以实现能源优化。对于用户提交的虚拟机(VM)组,我们根据虚拟机之间的流量和负载相关性重构了虚拟机关联图,并使用改进的多级k路分区算法对图进行了分区。结合数据中心拓扑,通过扩展PM群集确定VM和物理机(PM)的两层映射关系。实验结果表明,与其他相关算法相比,我们提出的算法可以保证更好的资源利用,控制违反服务水平协议(SLA)并节省大量能源。

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