• DocumentCode
    603704
  • Title

    Five resource allocation strategies for the cloud infrastructure

  • Author

    Xue Wang ; Razo, Miguel ; Tacca, Marco ; Ning So ; Fumagalli, Andrea

  • Author_Institution
    OpNeAR Lab., Univ. of Texas at Dallas, Richardson, TX, USA
  • fYear
    2013
  • fDate
    16-19 April 2013
  • Firstpage
    13
  • Lastpage
    18
  • Abstract
    As both cloud applications and infrastructure technologies become more advanced, there is a general expectation that cloud based applications are going to experience improved end-to-end performance assurance while maintaining a competitive cost of service. In this paper, the authors continue to explore the potential performance and cost advantages, which may originate when applying joint optimization resource allocation strategies to the cloud infrastructure in the presence of dynamic application requests. Five resource allocation strategies are defined and compared to estimate relative performance gains in a number of resource (network bandwidth, data center CPU, memory and storage) distribution scenarios.
  • Keywords
    cloud computing; computer centres; resource allocation; software performance evaluation; storage management; cloud applications; cloud based applications; cloud infrastructure technologies; competitive service cost maintenance; data center CPU; dynamic application requests; end-to-end performance assurance; joint optimization resource allocation strategies; memory; network bandwidth; storage; Availability; Bandwidth; Joints; Memory management; Optimization; Resource management; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Optical Network Design and Modeling (ONDM), 2013 17th International Conference on
  • Conference_Location
    Brest
  • Print_ISBN
    978-1-4799-0491-4
  • Type

    conf

  • Filename
    6524915