一种新的物理主机资源利用阈值边界管理策略

A New Physical Host Resource Utilization Thresholds Management Strategy

提出了一种新的物理主机资源利用阈值边界管理策略(Physical host resource utilization thresholds management strategy,RUT‑MS)。RUT‑MS把云数据中心的虚拟机迁移过程进一步划分为超负载主机检测、虚拟机选择、虚拟机放置第1阶段、低负载主机检测和虚拟机放置第2阶段。使用一种迭代权重线性回归方法来预测物理资源的阈值上限,避免超负载的物理主机数量的增加;采用最小能量消耗策略完成虚拟机选择过程;使用多维物理资源的均方根来确定其资源使用阈值下限,减少低负载物理主机数量。实验结果表明:RUT‑MS物理资源利用阈值边界管理策略使云数据中心的能量消耗和虚拟机迁移次数明显减少,SLA(Service level agreement)违规率和SLA及能量消耗联合指标只有少量的增加。

A new physical resource utilization thresholds management strategy called RUT‑MS for cloud data centers is proposed in this paper.In RUT‑MS,the virtual machine migration process is divided into five steps:Overloaded host status detection,virtual machine selection,the first virtual machine placement,under‑loaded host status detection and the second virtual machine placement phases.In overloading host detection,RUT‑MS uses an iterative weighted linear regression method to determine two utilization thresholds so that the performance degradation is avoided.Maximum power reduction policy(MPR)is adopted in virtual machine selection phase.A vector magnitude squared of multiple dimension resources is used to decide the low resource utilization thresholds and switch them to a power saving mode.Finally,RUT‑MS is evaluated using CloudSim with real‑world workload data.Simulation results show that RUT‑MS can reduce the energy cost incurred on the system due to migration.The reduced number of virtual machine migrations and improved energy‑efficiency are also obtained in our test.Moreover,the service level agreement(SLA)violation and SLA for energy united metrics are also good.