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文雨, 王伟平, 郭莉, 孟丹. 面向虚拟化基础设施的自动化能耗控制方法[J]. 计算机科学技术学报, 2014, 29(6): 1111-1122. DOI: 10.1007/s11390-014-1494-x
引用本文: 文雨, 王伟平, 郭莉, 孟丹. 面向虚拟化基础设施的自动化能耗控制方法[J]. 计算机科学技术学报, 2014, 29(6): 1111-1122. DOI: 10.1007/s11390-014-1494-x
Yu Wen, Wei-Ping Wang, Li Guo, Dan Meng. Automated Power Control for Virtualized Infrastructures[J]. Journal of Computer Science and Technology, 2014, 29(6): 1111-1122. DOI: 10.1007/s11390-014-1494-x
Citation: Yu Wen, Wei-Ping Wang, Li Guo, Dan Meng. Automated Power Control for Virtualized Infrastructures[J]. Journal of Computer Science and Technology, 2014, 29(6): 1111-1122. DOI: 10.1007/s11390-014-1494-x

面向虚拟化基础设施的自动化能耗控制方法

Automated Power Control for Virtualized Infrastructures

  • 摘要: 近期虚拟化环境的能耗控制问题吸引了大量关注.其中一个主要的挑战是在维持底层基础设施低能耗状态的同时,实现上层应用的服务级目标(Service-Level Objectives).然而,当前已有工作都不能有效解决这个问题.本文提出一种面向虚拟化环境的自动化能耗控制方法,并同时实现应用的服务级目标.我们方法的主要优点是,根据应用服务级目标精确的控制物理环境处理器频率和应用虚拟机的处理器频率份额分配.我们的方法基于控制理论和在线应用模型估计,能够自适应应用负载和虚拟环境的变化.此外,我们方法能够根据应用虚拟机在应用级和基础设施级的相关性,协调管理虚拟机能耗控制.实验评价证明,在同时实现应用服务级目标和维持底层环境低能耗方面,我们的方法优于三种现有方法.

     

    Abstract: Power control for virtualized environments has gained much attention recently. One of the major challenges is keeping underlying infrastructure in reasonably low power states and achieving service-level objectives (SLOs) of upper applications as well. Existing solutions, however, cannot effectively tackle this problem for virtualized environments. In this paper, we propose an automated power control solution for such scenarios in hope of making some progress. The major advantage of our solution is being able to precisely control the CPU frequency levels of a physical environment and the CPU power allocations among virtual machines with respect to the SLOs of multiple applications. Based on control theory and online model estimation, our solution can adapt to the variations of application power demands. Additionally, our solution can simultaneously manage the CPU power control for all virtual machines according to their dependencies at either the application-level or the infrastructure-level. The experimental evaluation demonstrates that our solution outperforms three state-of-the-art methods in terms of achieving the application SLOs with low infrastructure power consumption.

     

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