• DocumentCode
    3462491
  • Title

    Elastic Resource Allocation in the Cloud

  • Author

    Jieqian Wu ; BaoJian Zhou ; Depei Qian ; Ming Xie ; Wei Chen

  • Author_Institution
    Sino-German Joint Software Inst., Beihang Univ., Beijing, China
  • fYear
    2013
  • fDate
    3-5 Dec. 2013
  • Firstpage
    1338
  • Lastpage
    1342
  • Abstract
    In traditional cloud computing, elastic computing can be provided by increasing or decreasing the number of virtual machines (VM). However, the resource needed by applications change swiftly. This coarse-grained resource allocation approach is not a perfect way to satisfy the demand of the workload in short term. In this paper, we present a fine-grained resource allocation method in virtualized servers. This method uses a real-time control model in order to meet the demands of varying workload by sizing the VMs dynamically. We compare, evaluate, and analyze this approach. Experimental results confirm that this approach guarantees performance and resource efficiency for applications.
  • Keywords
    cloud computing; resource allocation; virtual machines; VM; cloud computing; coarse-grained resource allocation; elastic computing; elastic resource allocation; virtual machines; Cloud computing; Dynamic scheduling; Measurement; Resource management; Servers; Virtual machining; Virtualization; Cloud; Elastic resource allocation; Resource management; Virtualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Science and Engineering (CSE), 2013 IEEE 16th International Conference on
  • Conference_Location
    Sydney, NSW
  • Type

    conf

  • DOI
    10.1109/CSE.2013.198
  • Filename
    6755380