异构云环境下一种基于虚拟机CPU的能耗模型
首发时间:2019-03-01
摘要:随着数据中心能耗成本的不断提高,能耗监控成为当前云计算研究的重要课题。现代数据中心的异构性往往会导致产生的能耗差异巨大,针对这一问题,将传统的能耗监控技术与虚拟化技术相结合,提出了一种异构云环境下基于虚拟机CPU频率和核数的非线性能耗模型(Nonlinear energy consumption model based on CPU frequency and CPU cores of virtual machine in heterogeneous cloud environment,HFNM)。该模型考虑了数据中心的异构性特点,基于虚拟机CPU的频率和核数对能耗进行建模,为云计算数据中心的能耗监控问题提供了新的解决思路。实验结果表明,HFNM模型降低了数据中心异构性所导致的误差,能够对计算密集型工作负载下的虚拟机提供精确的能耗估计。
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An energy consumption model based on CPU of virtual machine in heterogeneous cloud environment
Abstract:With the increase of energy cost in data centers, energy consumption monitoring has become an important topic in current cloud computing research. The heterogeneity of modern data centers often leads to great differences in energy consumption. In view of this problem, this paper proposes a nonlinear energy consumption model based on CPU frequency and CPU cores of virtual machine(HFNM) in heterogeneous cloud environment by combining traditional technology of energy consumption monitoring with the technology of virtualization. This model considers the heterogeneity of data centers, and conducts the energy consumption model based on the CPU frequency and CPU cores of virtual machine, which provides a new solution for the energy monitoring of cloud data center. The experimental results show that HFNM can reduce errors caused by heterogeneity of data centers and can provide the accurate estimation of energy for virtual machines under compute-intensive workload.
Keywords: Cloud data center heterogeneous energy model virtual machine CPU
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