• DocumentCode
    123774
  • Title

    Energy-Efficient Virtual Machines Placement

  • Author

    De La Vigliotti, Albert P. M. ; Macedo Batista, Daniel

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Sao Paulo, Sao Paulo, Brazil
  • fYear
    2014
  • fDate
    5-9 May 2014
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Energy efficiency on computer systems is a topic that is gaining a lot of interest. Even more in the cloud computing era, where data centres consumption corresponds to near 1.5% of total world wide power consumption. In this paper we present two novel approaches for virtual machines (VMs) placement consolidation. The two approaches aim to maximize the placed VMs on a host and therefore minimize the number of hosts used on a cloud computing environment. The first proposed approach is based on the Knapsack problem and the second one is based on an Evolutionary Computation heuristic. Both strategies have shown consumed energy reduction starting from 40.33% and up to 92.21% compared to a strategy that does not consider energy efficiency.
  • Keywords
    cloud computing; computer centres; evolutionary computation; knapsack problems; power aware computing; virtual machines; VM; cloud computing environment; computer systems; consumed energy reduction; data centers consumption; energy-efficient virtual machines placement; evolutionary computation heuristic; knapsack problem; Cloud computing; Computational modeling; Containers; Libraries; Resource management; Virtual machining; Virtualization; cloud computing; green cloud; power efficiency; virtual machines consolidation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Networks and Distributed Systems (SBRC), 2014 Brazilian Symposium on
  • Conference_Location
    Florianopolis
  • Type

    conf

  • DOI
    10.1109/SBRC.2014.1
  • Filename
    6927113