• DocumentCode
    2876124
  • Title

    Quantifying Resiliency of IaaS Cloud

  • Author

    Ghosh, Rahul ; Longo, Federica ; Naik, Vijay K. ; Trivedi, Kishor S.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Duke Univ., Durham, NC, USA
  • fYear
    2010
  • fDate
    Oct. 31 2010-Nov. 3 2010
  • Firstpage
    343
  • Lastpage
    347
  • Abstract
    Cloud based services may experience changes - internal, external, large, small - at any time. Predicting and quantifying the effects on the quality-of-service during and after a change are important in the resiliency assessment of a cloud based service. In this paper, we quantify the resiliency of infrastructure-as-a-service (IaaS) cloud when subject to changes in demand and available capacity. Using a stochastic reward net based model for provisioning and servicing requests in a IaaS cloud, we quantify the resiliency of IaaS cloud w.r.t. two key performance measures - job rejection rate and provisioning response delay.
  • Keywords
    Internet; software architecture; stochastic processes; IaaS cloud; cloud based services; resiliency quantification; stochastic reward net based model; Analytical models; Clouds; Computational modeling; Delay; Markov processes; Steady-state;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reliable Distributed Systems, 2010 29th IEEE Symposium on
  • Conference_Location
    New Delhi
  • ISSN
    1060-9857
  • Print_ISBN
    978-0-7695-4250-8
  • Type

    conf

  • DOI
    10.1109/SRDS.2010.49
  • Filename
    5623413