• DocumentCode
    2182153
  • Title

    OCPA: An Algorithm for Fast and Effective Virtual Machine Placement and Assignment in Large Scale Cloud Environments

  • Author

    Zhenyun Zhuang ; Chun Guo

  • Author_Institution
    Salesforce.com, Inc., San Francisco, CA, USA
  • fYear
    2013
  • fDate
    16-19 Dec. 2013
  • Firstpage
    254
  • Lastpage
    259
  • Abstract
    Cloud Computing is increasingly being deployed as a fast and economic solution to various requests that require instantiating computing resources to serve customers´ need. Despite the distinctions among the three commonly accepted service models (i.e., IaaS, PaaS, and SaaS), any large scale cloud computing deployment requires the instantiation of multiple VMs (Virtual Machines) in a coordinated manner. These VMs may further need to be placed in multiple geographically distributed data centers, and users that are closer to a VM enjoy the benefits of smaller response time, higher bandwidth, hence better performance. Thus, how to appropriately place VMs and assign them to cloud users can have significant impact on the latter´s performance. In this work, we consider the problems of VM placement and assignment. Based on a set of unique design principles, we propose an effective and efficient solution which is referred to as OCPA (Opportunity Cost based VM Placement and Assignment). OCPA can achieve much better performance and the running time complexity is kept linear.
  • Keywords
    cloud computing; computer centres; virtual machines; OCPA; cloud computing; large scale cloud environments; linear time complexity; multiple VMs; multiple geographically distributed data centers; opportunity cost based VM placement and assignment; virtual machine assignment; virtual machine placement; Bandwidth; Cloud computing; Distributed databases; Measurement; Sociology; Statistics; Virtual machining; Cloud Computing; Opportunity Cost; Virtual Machine Placement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing and Big Data (CloudCom-Asia), 2013 International Conference on
  • Conference_Location
    Fuzhou
  • Print_ISBN
    978-1-4799-2829-3
  • Type

    conf

  • DOI
    10.1109/CLOUDCOM-ASIA.2013.81
  • Filename
    6821001