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Analysis of a Two-State Markov Fluid Model with 2 Buffers

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Computer Performance Engineering and Stochastic Modelling (EPEW 2023, ASMTA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14231))

Abstract

Single buffer Markov fluid models are well understood in the literature, but the extension of those results for multiple buffers is still an open research problem. In this paper we consider one of the simplest Markov fluid models (MFM) with 2 buffers of infinite capacity, where the fluid rates ensure that the fluid level of buffer 1 is never larger than fluid level of buffer 2. In spite of these restrictions, the stationary analysis is non straightforward with the available analysis tools. We provide an analysis approach based on the embedded time points at the busy-idle cycles of buffer 1.

This work is partially supported by the Hungarian Scientific Research Fund OTKA K-138208 project.

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Author information

Authors and Affiliations

  1. Technische Universität Dortmund, Dortmund, Germany

    Peter Buchholz

  2. Department of Networked Systems and Services, Budapest University of Technology and Economics, Budapest, Hungary

    Meszaros Andras & Miklos Telek

  3. ELKH-BME Information Systems Research Group, Budapest, Hungary

    Meszaros Andras & Miklos Telek

Authors
  1. Peter Buchholz
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  2. Meszaros Andras
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  3. Miklos Telek
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Corresponding author

Correspondence to Miklos Telek .

Editor information

Editors and Affiliations

  1. Università degli Studi della Campania, Caserta, Italy

    Mauro Iacono

  2. Università degli Studi di Messina, Messina, Italy

    Marco Scarpa

  3. Università Cattolica del Sacro Cuore, Brescia, Italy

    Enrico Barbierato

  4. Università degli Studi di Messina, Messina, Italy

    Salvatore Serrano

  5. Università del Piemonte Orientale, Alessandria, Italy

    Davide Cerotti

  6. Universita degli Studi di Messina, Messina, Italy

    Francesco Longo

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Buchholz, P., Andras, M., Telek, M. (2023). Analysis of a Two-State Markov Fluid Model with 2 Buffers. In: Iacono, M., Scarpa, M., Barbierato, E., Serrano, S., Cerotti, D., Longo, F. (eds) Computer Performance Engineering and Stochastic Modelling. EPEW ASMTA 2023 2023. Lecture Notes in Computer Science, vol 14231. Springer, Cham. https://doi.org/10.1007/978-3-031-43185-2_4

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  • DOI: https://doi.org/10.1007/978-3-031-43185-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43184-5

  • Online ISBN: 978-3-031-43185-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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