• DocumentCode
    1789330
  • Title

    Towards multi-resource physical machine provisioning for IaaS clouds

  • Author

    Lei Wei ; Bingsheng He ; Chuan Heng Foh

  • Author_Institution
    Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
  • fYear
    2014
  • fDate
    10-14 June 2014
  • Firstpage
    3469
  • Lastpage
    3472
  • Abstract
    Virtualization has been an enabling technology for IaaS (Infrastructure as a Service) Clouds. Physical machine (PM) provisioning is a key problem for IaaS cloud providers on their resource utilization and quality of service to users. Proper provisioning is able to ensure the service quality while conserving unnecessary power consumption from over-provisioned PMs. However, the effectiveness of PM provisioning in current IaaS providers such as Amazon and Rackspace is severely limited by that they offer virtual machines with proportional resource provisioning on different resource types (including CPU, memory and disk etc). Such a rigid offering cannot satisfy diversified user applications in the cloud, and can cause significant over-provision on PMs in order to satisfy users´ requirement on all resource types. This paper argues a more flexible approach that IaaS providers should offer virtual machines with flexible combinations on multiple resource types. We further formulate the problem of multiple resource virtual machine allocations for IaaS clouds, and develop analytical models to predict the suitable number of PMs while satisfying a predefined quality-of-service requirement. Experiments show that the proposed approach can significantly increase the resource utilization, with a reduction on the number of active PMs by 27% on average.
  • Keywords
    cloud computing; quality of service; resource allocation; virtual machines; virtualisation; Amazon; IaaS clouds; PM provisioning; Rackspace; infrastructure as a service clouds; multiresource physical machine provisioning; quality of service; resource provisioning; resource utilization; resource virtual machine allocations; virtualization; Analytical models; Computational modeling; Markov processes; Prediction algorithms; Quality of service; Resource management; Virtual machining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (ICC), 2014 IEEE International Conference on
  • Conference_Location
    Sydney, NSW
  • Type

    conf

  • DOI
    10.1109/ICC.2014.6883858
  • Filename
    6883858