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A modeling-based approach for dependability analysis of a constellation of satellites

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Abstract

Satellite constellations play critical roles across various sectors, encompassing communication, Earth observation and space exploration. Ensuring the dependable operation of these constellations is of utmost importance. This paper introduces a dependability modeling approach using stochastic Petri nets to analyze satellite constellations. The primary focus is on improving operational efficiency through the assessment of availability, reliability and maintainability. The approach helps satellite designers make informed decisions when selecting constellation configurations by assessing various dependability metrics. Using a global navigation satellite system as a case study, we conduct extensive numerical experiments to evaluate the feasibility of our approach. The results demonstrate quantitatively the significant impact of redundant components on both reliability and availability. They also illustrate how utilizing satellites in repair and operational orbits can influence these metrics and highlight the direct correlation between reliability and maintainability.

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Author notes

  1. Daniel Farias, Bruno Nogueira, Ivaldir Farias Júnior and Ermeson Andrade have contributed equally to this work.

Authors and Affiliations

  1. Departamento de Computação, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil

    Daniel Farias & Ermeson Andrade

  2. Instituto de Computação, Universidade Federal de Pernambuco, Maceió, Alagoas, Brazil

    Bruno Nogueira

  3. Programa de Pós-Graduação em Engenharia da Computação, Universidade de Pernambuco, Recife, Pernambuco, Brazil

    Bruno Nogueira & Ivaldir Farias Júnior

Authors
  1. Daniel Farias
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  2. Bruno Nogueira
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  3. Ivaldir Farias Júnior
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  4. Ermeson Andrade
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Correspondence to Ermeson Andrade.

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Communicated by Robert Pettit.

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Farias, D., Nogueira, B., Júnior, I.F. et al. A modeling-based approach for dependability analysis of a constellation of satellites. Softw Syst Model 24, 209–224 (2025). https://doi.org/10.1007/s10270-024-01197-7

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  • DOI: https://doi.org/10.1007/s10270-024-01197-7

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