• DocumentCode
    3739547
  • Title

    Energy Efficient Virtual Machine Consolidation under Uncertain Input Parameters for Green Data Centers

  • Author

    Enrica Zola;Andreas J. Kassler

  • Author_Institution
    Dept. of Network Eng., UPC, Barcelona, Spain
  • fYear
    2015
  • Firstpage
    436
  • Lastpage
    439
  • Abstract
    Reducing the energy consumption of data centers and the Cloud is very important in order to lower CO_2 footprint and operational cost (OPEX) of a Cloud operator. To this extent, it becomes crucial to minimise the energy consumption by consolidating the number of powered-on physical servers that host the given virtual machines (VMs). In this work, we propose a novel approach to the energy efficient VM consolidation problem by applying Robust Optimisation Theory. We develop a mathematical model as a robust Mixed Integer Linear Program under the assumption that the input to the problem (e.g. resource demands of the VMs) is not known precisely, but varies within given bounds. A numerical evaluation shows that our model allows the Cloud Operator to tradeoff between the power consumption and the protection from more severe and unlikely deviations of the uncertain input.
  • Keywords
    "Power demand","Robustness","Uncertainty","Energy consumption","Optimization","Data models","Cloud computing"
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing Technology and Science (CloudCom), 2015 IEEE 7th International Conference on
  • Type

    conf

  • DOI
    10.1109/CloudCom.2015.15
  • Filename
    7396188