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Reliability Evaluation of Reconfigurable NMR Architecture Supported with Hot Standby Spare: Markov Modeling and Formulation

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Model-Based Safety and Assessment (IMBSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12297))

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Abstract

Reliability is a major issue for fault-tolerant systems used in critical applications. N-modular redundancy (NMR) is one of the traditional approaches used for fault masking in fault-tolerant systems. Reconfigurable NMR architecture supported with hot or cold standby spares is a common industrial method. So far, no systematic method for creating the Markov model of reconfigurable NMR systems supported with hot standby spares has been presented. Likewise, there is no explicit parametric formula for the reliability of these systems in the literature. This paper focuses on two issues: the systematic construction of the Markov model of reconfigurable NMR system, and its evaluation through a precise and explicit formula introduces in this paper. The introduced formula gives for system designer a good view of reliability behaviour of the reconfigurable NMR systems.

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References

  1. Cathebras, G.: Dependability: a challenge for electrical medical implants. In: IEEE International Conference of Engineering in Medicine and Biology Society (EMBC), Buenos Aires (2010)

    Google Scholar 

  2. Yeh, Y.: Triple-triple redundant 777 primary flight computer. In: IEEE Aerospace Applications Conference, Aspen, CO (1996)

    Google Scholar 

  3. Latif-Shabgahi, G., Bass, J.M., Bennett, S.: A taxonomy for software voting algorithms used in safety-critical systems. IEEE Trans. Reliab. 53(3), 319–328 (2004)

    Article  Google Scholar 

  4. Butler, R.W., Johnson, S.C.: Techniques for modeling the reliability of fault-tolerant systems with the Markov state-space approach, vol. 1348. National Aeronautics and Space Administration, Langley Research Center, Lindbergh Way, Hampton, VA, United States (1995)

    Google Scholar 

  5. Dubrova, E.: Fault-Tolerant Design. Springer, Heidelberg (2012). https://doi.org/10.1007/978-1-4614-2113-9

    Book  MATH  Google Scholar 

  6. Dugan, J.B., Trivedi, K.S., Smotherman, M.K., Geist, R.M.: The hybrid automated reliability predictor. J. Guidance Control Dyn. 9(3), 319–331 (1986)

    Article  Google Scholar 

  7. Liu, Z., et al.: RAMS analysis of hybrid redundancy system of subsea blowout preventer based on stochastic Petri Nets. Int. J. Secur. Appl. 7(4), 159–166 (2013)

    Google Scholar 

  8. Cai, B., Liu, Y., Liu, Z., Tian, X., Li, H., Ren, C.: Reliability analysis of subsea blowout preventer control systems subjected to multiple error shocks. J. Loss Prevent. Process Ind. 25(6), 1044–1054 (2012)

    Article  Google Scholar 

  9. Popstojanova, K.G., Mathur, A.P., Trivedi, K.S.: Comparison of architecture based software reliability models, In: 12th International Symposium on Software Reliability Engineering, Hong Kong (2001)

    Google Scholar 

  10. Distefano, S., Longo, F., Trivedi, K.S.: Investigating dynamic reliability and availability through state-space models. Comput. Math Appl. 64(12), 3701–3716 (2012)

    Article  MathSciNet  Google Scholar 

  11. Pukite, J., Pukite, P.: Markov Modeling for Reliability, Maintainability, Safety, and Supportability Analyses of Complex Computer Systems, Series on Engineering of Complex Computer Systems. IEEE Press, New York (1998)

    Google Scholar 

  12. Butler, R.W.: A primer on architectural level fault tolerance. National Aeronautics and Space Administration, Langley Research Center, Lindbergh Way, Hampton, VA, United States (2008)

    Google Scholar 

  13. Butler, R.W., Hayhurst, K.J., Johnson, S.C.: A note about HARP’s state trimming method, National Aeronautics and Space Administration, Langley Research Center, Lindbergh Way, Hampton, VA, United States (1998)

    Google Scholar 

  14. Mathur, F.P., Avižienis, A.: Reliability analysis and architecture of a hybrid-redundant digital system: generalized triple modular redundancy with self-repair. In: Spring Joint Computer Conference. ACM (1969)

    Google Scholar 

  15. Zhang, K., Bedette, G., DeMara, R.F.: Triple Modular Redundancy with Standby (TMRSB) supporting dynamic resource reconfiguration. In: IEEE Autotestcon, Anaheim, CA (2006)

    Google Scholar 

  16. Zhe, Z., Daxin, L., Zhengxian, W., Changsong, S.: Research on triple modular redundancy dynamic fault-tolerant system model. In: First International Multi-Symposiums on Computer and Computational Sciences. IMSCCS, Hanzhou, Zhejiang (2006)

    Google Scholar 

  17. Walter, M., Gouberman, A., Riedl, M., Schuster, J., Siegle, M.: LARES-A novel approach for describing system reconfigurability in dependability models of fault-tolerant systems. In: European Safety and Reliability Conference, Valencia, Spain (2009)

    Google Scholar 

  18. Chellappan, C., Vijayalakshmi, G.: Dependability modeling and analysis of hybrid redundancy systems. Int. J. Qual. Reliab. Manag. 26(1), 76–96 (2009)

    Article  Google Scholar 

  19. Chellappan, C., Vijayalakshmi, G.: Dependability analysis of hybrid redundancy systems using fuzzy approach. Int. J. Reliab. Q. Saf. Eng. 17(4), 331–350 (2010)

    Article  Google Scholar 

  20. Maire, R.A., Reibman, A.L., Trivedi, K.S.: Transient analysis of acyclic Markov Chains. Perform. Eval. 7(3), 175–194 (1987)

    Article  MathSciNet  Google Scholar 

  21. Aslansefat, K., Latif-Shabgahi, G.: A new method in drawing reliability markov model of reconfigurable TMR systems with frequency formulations. In: 5th Iranian Conference on Electrical & Electronics Engineering (ICEEE), Gonabad, Iran (2013)

    Google Scholar 

  22. Aslansefat, K., Latif-Shabgahi, G.: Systematic methods in Markov reliability modelling of reconfigurable NMR architecture with cold standby spare. In: 16th Iranian Electrical Engineering Students Conference, Kazerun, Iran (2013)

    Google Scholar 

  23. Aslansefat, K.: A novel approach for reliability and safety evaluation of control systems with dynamic fault tree. MSc. Thesis, Shahid Beheshti University (2014)

    Google Scholar 

  24. Johnson, B.: Design and Analysis of Fault-Tolerant Digital Systems, 6th edn. Addison-Wesley, Boston (1989)

    Google Scholar 

  25. Aslansefat, K., Marques, F., Mendonça, R., Barata, J.: A Markov process-based approach for reliability evaluation of the propulsion system in multi-rotor drones. In: Camarinha-Matos, L.M., Almeida, R., Oliveira, J. (eds.) DoCEIS 2019. IAICT, vol. 553, pp. 91–98. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-17771-3_8

    Chapter  Google Scholar 

  26. Aslansefat, K., Latif-Shabgahi, G.R.: A hierarchical approach for dynamic fault trees solution through Semi-Markov process. IEEE Trans. Reliab. (Early Access). https://doi.org/10.1109/tr.2019.2923893

  27. Kabir, S., Aslansefat, K., Sorokos, I., Papadopoulos, Y., Gheraibia, Y.: A conceptual framework to incorporate complex basic events in HiP-HOPS. In: Papadopoulos, Y., Aslansefat, K., Katsaros, P., Bozzano, M. (eds.) IMBSA 2019. LNCS, vol. 11842, pp. 109–124. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-32872-6_8

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, University of Hull, Hull, UK

    Koorosh Aslansefat

  2. Department of Electrical Engineering, Shahid Beheshti University, Tehran, Iran

    Gholamreza Latif-Shabgahi & Mehrdad Mohammadi

Authors
  1. Koorosh Aslansefat
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  2. Gholamreza Latif-Shabgahi
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  3. Mehrdad Mohammadi
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Corresponding author

Correspondence to Koorosh Aslansefat .

Editor information

Editors and Affiliations

  1. Siemens AG, Munich, Bayern, Germany

    Marc Zeller

  2. University of Applied Sciences Rosenheim, Rosenheim, Germany

    Kai Höfig

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Aslansefat, K., Latif-Shabgahi, G., Mohammadi, M. (2020). Reliability Evaluation of Reconfigurable NMR Architecture Supported with Hot Standby Spare: Markov Modeling and Formulation. In: Zeller, M., Höfig, K. (eds) Model-Based Safety and Assessment. IMBSA 2020. Lecture Notes in Computer Science(), vol 12297. Springer, Cham. https://doi.org/10.1007/978-3-030-58920-2_4

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  • DOI: https://doi.org/10.1007/978-3-030-58920-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58919-6

  • Online ISBN: 978-3-030-58920-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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