Composing hierarchical stochastic model from SysML for system availability analysis

Fumio Machida, Jianwen Xiang, Kumiko Tadano, Yoshiharu Maeno

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Comprehensive analytic model for system availability analysis often confronts the largeness issue where a system designer cannot easily handle the model and the solution is not given in a feasible solution time. Hierarchical decomposition of a large state-space model gives a promising solution to the largeness issue when the model is decomposable. However, the decomposability of analytic model is not always manually tractable especially when the model is generated in an automated manner. In this paper, we propose an automated model composition technique from a system design to a hierarchical stochastic model which is the judicious combination of combinatorial and state-space models. In particular, from SysML-based system specifications, a top-level fault tree and associated stochastic reward nets are automatically generated in hierarchical manner. The obtained hierarchical stochastic model can be solved analytically considerably faster than monolithic state-space models. Through an illustrative example of three-tier web application system on a virtualized infrastructure, the accuracy and efficiency of the solution are evaluated in comparison to a monolithic state space model and a static fault tree.

Original languageEnglish
Title of host publication2013 IEEE 24th International Symposium on Software Reliability Engineering, ISSRE 2013
Pages51-60
Number of pages10
DOIs
Publication statusPublished - 1 Dec 2013
Event2013 IEEE 24th International Symposium on Software Reliability Engineering, ISSRE 2013 - Pasadena, CA, United States
Duration: 4 Nov 20137 Nov 2013

Publication series

Name2013 IEEE 24th International Symposium on Software Reliability Engineering, ISSRE 2013

Conference

Conference2013 IEEE 24th International Symposium on Software Reliability Engineering, ISSRE 2013
CountryUnited States
CityPasadena, CA
Period4/11/137/11/13

Keywords

  • automated model composition
  • availability analysis
  • model decomposition
  • stochastic model
  • web application system

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  • Cite this

    Machida, F., Xiang, J., Tadano, K., & Maeno, Y. (2013). Composing hierarchical stochastic model from SysML for system availability analysis. In 2013 IEEE 24th International Symposium on Software Reliability Engineering, ISSRE 2013 (pp. 51-60). [6698904] (2013 IEEE 24th International Symposium on Software Reliability Engineering, ISSRE 2013). https://doi.org/10.1109/ISSRE.2013.6698904