• DocumentCode
    707474
  • Title

    Energy efficient resource allocation for heterogeneous cloud workloads

  • Author

    Kaur, Prabhjot ; Kaur, Pankaj Deep

  • Author_Institution
    CSE Dept., Guru Nanak Dev Univ., Jalandhar, India
  • fYear
    2015
  • fDate
    11-13 March 2015
  • Firstpage
    1319
  • Lastpage
    1322
  • Abstract
    Although cloud computing is now becoming more advanced and matured as many companies have released their own computing platforms to provide services to public, but the research on cloud computing is still in its infancy. Apart from many other challenges of cloud computing, efficient management of energy is one of the most challenging research issues. In this paper we review the existing algorithm of dynamic resource provisioning and allocation algorithms and holistically work to boost data center energy efficiency and performance. This particular paper purposes a) heterogeneous workload and its implication on data center´s energy efficiency b) solving the problem of VM resource scheduling to cloud applications.
  • Keywords
    cloud computing; computer centres; energy conservation; resource allocation; scheduling; VM resource scheduling; data center energy efficiency; data center performance; energy management; heterogeneous cloud workload; heterogeneous workload; resource allocation; resource allocation algorithm; resource provisioning algorithm; virtual machines; Cloud computing; Dynamic scheduling; Heuristic algorithms; Processor scheduling; Resource management; Servers; Virtual machining; Cloud Computing; Load Balancing; Skewness; Virtual Machine (VM);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing for Sustainable Global Development (INDIACom), 2015 2nd International Conference on
  • Conference_Location
    New Delhi
  • Print_ISBN
    978-9-3805-4415-1
  • Type

    conf

  • Filename
    7100464