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Sensitivity Analysis of Performability Model to Evaluate PBFT Systems

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Advanced Information Networking and Applications (AINA 2024)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 204))

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Abstract

The evaluation of performance and availability of consensus protocols used in distributed networks is a crucial part in the development of tailored solutions for diversified applications. When building an analytical model for performability evaluation, the sensitivity analysis of the model parameters is a necessary step to determine the output variance at the variation of the input parameters. The sensitivity analysis performed in this work shows that the input parameters of the analyzed performability model have a highly non-linear effect on the considered performability metrics, determining a large variance on the output for small variation of the inputs.

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Author information

Authors and Affiliations

  1. Computer Science Division, University of Camerino, Camerino, Italy

    Marco Marcozzi

  2. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Marco Marcozzi

  3. Department of Information Engineering, Computer Science and Mathematics, University of L’Aquila, L’Aquila, Italy

    Antinisca Di Marco

  4. Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy

    Leonardo Mostarda

Authors
  1. Marco Marcozzi
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  2. Antinisca Di Marco
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  3. Leonardo Mostarda
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Corresponding author

Correspondence to Marco Marcozzi .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Marcozzi, M., Di Marco, A., Mostarda, L. (2024). Sensitivity Analysis of Performability Model to Evaluate PBFT Systems. In: Barolli, L. (eds) Advanced Information Networking and Applications. AINA 2024. Lecture Notes on Data Engineering and Communications Technologies, vol 204. Springer, Cham. https://doi.org/10.1007/978-3-031-57942-4_12

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