• DocumentCode
    1919699
  • Title

    UVMPM: A Unitary Approach for VM Power Metering Based on Performance Profiling

  • Author

    Yang, Hailong ; Zhao, Qi ; Luan, Zhongzhi ; Qian, Depei

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Beihang Univ., Beijing, China
  • fYear
    2012
  • fDate
    10-13 Sept. 2012
  • Firstpage
    614
  • Lastpage
    615
  • Abstract
    Energy consumption in contemporary data centers is continuously surging in an unsustainable way, and tremendous efforts have been devoted both from industry and academia to address this issue. The pervasive utilization of virtual machines (VMs) in Cloud computing offers the service provider an opportunity to consolidate various workloads onto fewer servers, thus improving resource utilization as well as eliminating idle power consumption. Meanwhile, over-provisioning of VMs on individual servers may cause more power to be consumed by the cooling systems and imbalance on power distribution systems, which increases the possibility of system failures due to overheating. Therefore, power capping is widely adopted to reinforce the upper-bound power consumption of a single server taking the advantage of dynamic frequency voltage scaling (DVFS) technology which is extensively supported by the server manufacturers.
  • Keywords
    cloud computing; computer centres; cooling; energy consumption; power aware computing; ubiquitous computing; virtual machines; DVFS technology; UVMPM; VM power metering; cloud computing; contemporary data centers; cooling systems; dynamic frequency voltage scaling; energy consumption; performance profiling; pervasive utilization; power distribution systems; unitary approach; virtual machines; Benchmark testing; Power demand; Power measurement; Servers; Virtual machining; KVM; cloud computing; performance profiling; power capping; power metering; power model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Processing Workshops (ICPPW), 2012 41st International Conference on
  • Conference_Location
    Pittsburgh, PA
  • ISSN
    1530-2016
  • Print_ISBN
    978-1-4673-2509-7
  • Type

    conf

  • DOI
    10.1109/ICPPW.2012.95
  • Filename
    6337543