• DocumentCode
    690866
  • Title

    Reliability analysis based on jump diffusion models for an open source cloud computing

  • Author

    Tamura, Yoshinobu ; Miyahara, Hidekazu ; Yamada, Shigeru

  • Author_Institution
    Grad. Sch. of Sci. & Eng., Yamaguchi Univ., Ube, Japan
  • fYear
    2012
  • fDate
    10-13 Dec. 2012
  • Firstpage
    752
  • Lastpage
    756
  • Abstract
    A cloud computing is also attracting attention as a network service to share the computing resources such as networks, servers, storage, applications, and services. We focus on a cloud computing environment by using open source software such as OpenStack and Eucalyptus because of the unification management of data, and low cost. In this paper, we propose a new approach to software reliability assessment based on a jump diffusion model based on the stochastic differential equations in order to consider the interesting aspect of the numbers of components and users. Also, actual software fault-count data are analyzed in order to show numerical examples of software reliability assessment. Moreover, this paper shows that the proposed method of reliability analysis can assist quality improvement for the cloud computing.
  • Keywords
    cloud computing; data analysis; differential equations; public domain software; software quality; software reliability; stochastic processes; Eucalyptus; OpenStack; computing resource sharing; data unification management; jump diffusion model; network service; open source cloud computing environment; open source software; software fault-count data analysis; software quality improvement; software reliability assessment; stochastic differential equations; Cloud computing; Computational modeling; Mathematical model; Software reliability; Stochastic processes; Cloud computing; jump diffusion modeling; open source software; reliability analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IEEM), 2012 IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Type

    conf

  • DOI
    10.1109/IEEM.2012.6837840
  • Filename
    6837840