• DocumentCode
    3575184
  • Title

    Cost-Optimized Resource Provision for Cloud Applications

  • Author

    Yuxi Shen ; Haopeng Chen ; Lingxuan Shen ; Cheng Mei ; Xing Pu

  • Author_Institution
    REINS Group, Shanghai Jiao Tong Univ., Shanghai, China
  • fYear
    2014
  • Firstpage
    1060
  • Lastpage
    1067
  • Abstract
    With an increasing number of cloud providers starting to offer virtual resource leasing services, application providers have more choices when requiring resources. But how to achieve the most cost-optimized resource solution is still a challenge. To address this problem, we propose a cost optimized resource provision approach which achieves the cost saving target for application providers. In our approach, we figure out the projection between workload and VM amount according to predicted workload. By exploiting pricing policies of existing cloud providers, our approach presents a hybrid resource provision solution, which involve instances of different prices and leasing durations. The experiment results demonstrate that our approach achieves the cost-saving goal with few SLA violations and little resource waste.
  • Keywords
    cloud computing; optimisation; pricing; SLA violations; cloud applications; cloud providers; cost saving target; cost-optimized resource provision; hybrid resource provision solution; pricing policies; Cloud computing; Monitoring; Prediction algorithms; Predictive models; Pricing; Time factors; Virtual machining; Cloud computing; Cost-optimized; Pricing; Resource provision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computing and Communications, 2014 IEEE 6th Intl Symp on Cyberspace Safety and Security, 2014 IEEE 11th Intl Conf on Embedded Software and Syst (HPCC,CSS,ICESS), 2014 IEEE Intl Conf on
  • Print_ISBN
    978-1-4799-6122-1
  • Type

    conf

  • DOI
    10.1109/HPCC.2014.179
  • Filename
    7056875