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Runtime Observer Pairs and Bayesian Network Reasoners On-board FPGAs: Flight-Certifiable System Health Management for Embedded Systems

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Book cover Runtime Verification (RV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8734))

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Abstract

Safety-critical systems, like Unmanned Aerial Systems (UAS) that must operate totally autonomously, e.g., to support ground-based emergency services, must also provide assurance they will not endanger human life or property in the air or on the ground. Previously, a theoretical construction for paired synchronous and asynchronous runtime observers with Bayesian reasoning was introduced that demonstrated the ability to handle runtime assurance within the strict operational constraints to which the system must adhere. In this paper, we show how to instantiate and implement temporal logic runtime observers and Bayesian network diagnostic reasoners that use the observers’ outputs, on-board a field-standard Field Programmable Gate Array (FPGA) in a way that satisfies the strict flight operational standards of Realizability, Responsiveness, and Unobtrusiveness. With this type of compositionally constructed diagnostics framework we can develop compact, hierarchical, and highly expressive health management models for efficient, on-board fault detection and system monitoring. We describe an instantiation of our System Health Management (SHM) framework, rt-R2U2, on standard FPGA hardware, which is suitable to be deployed on-board a UAS. We run our system with a full set of real flight data from NASA’s Swift UAS, and highlight a case where our runtime SHM framework would have been able to detect and diagnose a fault from subtle evidence that initially eluded traditional real-time diagnosis procedures.

Additional artifacts to enable reproducibility are available at http://research.kristinrozier.com/ RV14.html. This work was supported in part by ARMD 2014 Seedling Phase I and Universities Space Research Association under NASA Cooperative Agreement, International Research Initiative for Innovation in Aerospace Methods and Technologies (I3AMT), NNX12AK33A.

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References

  1. Alur, R., Henzinger, T.A.: Real-time Logics: Complexity and Expressiveness. In: LICS, pp. 390–401. IEEE Computer Society Press (1990)

    Google Scholar 

  2. Chavira, M., Darwiche, A.: Compiling Bayesian networks with local structure. In: Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI), pp. 1306–1312 (2005)

    Google Scholar 

  3. Darwiche, A.: A differential approach to inference in Bayesian networks. Journal of the ACM 50(3), 280–305 (2003)

    Article  MathSciNet  Google Scholar 

  4. Darwiche, A.: Modeling and reasoning with Bayesian networks. In: Modeling and Reasoning with Bayesian Networks (2009)

    Google Scholar 

  5. Drusinsky, D.: The temporal rover and the ATG rover. In: Havelund, K., Penix, J., Visser, W. (eds.) SPIN 2000. LNCS, vol. 1885, pp. 323–330. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  6. Ippolito, C., Espinosa, P., Weston, A.: Swift UAS: An electric UAS research platform for green aviation at NASA Ames Research Center. In: CAFE EAS IV (April 2010)

    Google Scholar 

  7. Johnson, S., Gormley, T., Kessler, S., Mott, C., Patterson-Hine, A., Reichard, K., Philip Scandura, J.: System Health Management: with Aerospace Applications. Wiley & Sons (2011)

    Google Scholar 

  8. Majzoobi, M., Pittman, R.N., Forin, A.: gNOSIS: Mining FPGAs for verification (2011)

    Google Scholar 

  9. Mengshoel, O.J., Chavira, M., Cascio, K., Poll, S., Darwiche, A., Uckun, S.: Probabilistic model-based diagnosis: An electrical power system case study. IEEE Trans. on Systems, Man and Cybernetics, Part A: Systems and Humans 40(5), 874–885 (2010)

    Article  Google Scholar 

  10. Meredith, P.O., Jin, D., Griffith, D., Chen, F., Roşu, G.: An overview of the mop runtime verification framework. International Journal on Software Tools for Technology Transfer 14(3), 249–289 (2012)

    Article  Google Scholar 

  11. Musliner, D., Hendler, J., Agrawala, A.K., Durfee, E., Strosnider, J.K., Paul, C.J.: The challenges of real-time AI. IEEE Computer 28, 58–66 (1995), citeseer.comp.nus.edu.sg/article/musliner95challenges.html

    Article  Google Scholar 

  12. Pearl, J.: A constraint propagation approach to probabilistic reasoning. In: UAI, pp. 31–42. AUAI Press (1985)

    Google Scholar 

  13. Pellizzoni, R., Meredith, P., Caccamo, M., Rosu, G.: Hardware runtime monitoring for dependable COTS-based real-time embedded systems. In: RTSS, pp. 481–491 (2008)

    Google Scholar 

  14. Pike, L., Wegmann, N., Niller, S., Goodloe, A.: Copilot: monitoring embedded systems. Innovations in Systems and Software Engineering 9(4), 235–255 (2013)

    Article  Google Scholar 

  15. Reinbacher, T., Rozier, K.Y., Schumann, J.: Temporal-logic based runtime observer pairs for system health management of real-time systems. In: Ábrahám, E., Havelund, K. (eds.) TACAS 2014. LNCS, vol. 8413, pp. 357–372. Springer, Heidelberg (2014)

    Google Scholar 

  16. Schumann, J., Mbaya, T., Mengshoel, O.J., Pipatsrisawat, K., Srivastava, A., Choi, A., Darwiche, A.: Software health management with Bayesian networks. Innovations in Systems and Software Engineering 9(2), 1–22 (2013)

    Google Scholar 

  17. Schumann, J., Rozier, K.Y., Reinbacher, T., Mengshoel, O.J., Mbaya, T., Ippolito, C.: Towards real-time, on-board, hardware-supported sensor and software health management for unmanned aerial systems. In: Proceedings of the 2013 Annual Conference of the Prognostics and Health Management Society (PHM 2013), pp. 381–401 (October 2013)

    Google Scholar 

  18. Srivastava, A.N., Schumann, J.: Software health management: a necessity for safety critical systems. Innovations in Systems and Software Engineering 9(4), 219–233 (2013)

    Article  Google Scholar 

  19. Tabakov, D., Rozier, K.Y., Vardi, M.Y.: Optimized temporal monitors for SystemC. Formal Methods in System Design 41(3), 236–268 (2012)

    Article  MATH  Google Scholar 

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Geist, J., Rozier, K.Y., Schumann, J. (2014). Runtime Observer Pairs and Bayesian Network Reasoners On-board FPGAs: Flight-Certifiable System Health Management for Embedded Systems. In: Bonakdarpour, B., Smolka, S.A. (eds) Runtime Verification. RV 2014. Lecture Notes in Computer Science, vol 8734. Springer, Cham. https://doi.org/10.1007/978-3-319-11164-3_18

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  • DOI: https://doi.org/10.1007/978-3-319-11164-3_18

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11163-6

  • Online ISBN: 978-3-319-11164-3

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