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An Analytical Framework to Deal with Changing Points and Variable Distributions in Quality Assessment

In: Principles of Performance and Reliability Modeling and Evaluation

Author

Listed:
  • Dario Bruneo

    (Università degli Studi di Messina)

  • Salvatore Distefano

    (Higher Institute for Information Technology and Information Systems Kazan Federal University
    Università degli Studi di Messina)

  • Francesco Longo

    (Università degli Studi di Messina)

  • Marco Scarpa

    (Università degli Studi di Messina)

Abstract

Nonfunctional properties such as dependability and performance have growing impact on the design of a broad range of systems and services, where tighter constraints and stronger requirements have to be met. This way, aspects such as dependencies or interference, quite often neglected, now have to be taken into account due to the higher demand in terms of quality. In this chapter, we associate such aspects with operating conditions for a system, proposing an analytical framework to evaluate the effects of condition changing to the system quality properties. Starting from the phase type expansion technique, we developed a fitting algorithm able to catch the behavior of the system at changing points, implementing a codomain memory policy forcing the continuity of the observed quantity when operating conditions change. Then, to also deal with the state-space explosion problem of the underlying stochastic process, we resort to Kronecker algebra providing a tool able to evaluate, both in transient and steady states, nonfunctional properties of systems affected by variable operating conditions. Some examples from different domains are discussed to demonstrate the effectiveness of the proposed framework and its suitability to a wide range of problems.

Suggested Citation

  • Dario Bruneo & Salvatore Distefano & Francesco Longo & Marco Scarpa, 2016. "An Analytical Framework to Deal with Changing Points and Variable Distributions in Quality Assessment," Springer Series in Reliability Engineering, in: Lance Fiondella & Antonio Puliafito (ed.), Principles of Performance and Reliability Modeling and Evaluation, pages 27-48, Springer.
  • Handle: RePEc:spr:ssrchp:978-3-319-30599-8_2
    DOI: 10.1007/978-3-319-30599-8_2
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