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IMPROVING ACCURACY OF VIRTUAL MACHINE POWER MODEL BY RELATIVE-PMC BASED HEURISTIC SCHEDULING

机译:基于相对PMC的启发式调度提高虚拟机功率模型的精度

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Conventional utilization-based power model is effective for measuring the power consumption of physical machines. However, in virtualized environments its accuracy cannot be guaranteed because of the recursive resource accessing among multiple virtual machines. In this paper, we present a novel virtual machine scheduling algorithm, which uses Performance-Monitor-Counter as heuristic information to compensate the recursive power consumption. Theoretical analysis indicates that the error of virtual machine power model can be quantitative bounded when using the proposed scheduling algorithm. Extensive experiments based on standard benchmarks show that the error of virtual machine power measurements can be significantly reduced comparing with the classic credit-based scheduling algorithm.
机译:传统的基于利用率的功率模型对于测量物理机的功耗非常有效。但是,在虚拟化环境中,由于在多个虚拟机之间进行递归资源访问,因此无法保证其准确性。在本文中,我们提出了一种新颖的虚拟机调度算法,该算法使用Performance-Monitor-Counter作为启发式信息来补偿递归功耗。理论分析表明,使用该调度算法可以对虚拟机功率模型的误差进行定量界定。基于标准基准的大量实验表明,与传统的基于信用的调度算法相比,虚拟机功率测量的误差可以大大降低。

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