Modeling and Simulating Mutual Testing in Complex Systems by Using Petri Nets

Автор: Viktor Mashkov, Volodymyr Lytvynenko, Irina Lurie

Журнал: International Journal of Image, Graphics and Signal Processing @ijigsp

Статья в выпуске: 6 vol.15, 2023 года.

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The paper tackles the problem of performing mutual testing in complex systems. It is assumed that units of complex systems can execute tests on each other. Tests among system units are part of system diagnosis that can be carried out both before and during system operation. The paper considers the case when tests are executed during system operation. Modelling and simulating mutual tests will allow evaluation of the efficiency of using joint testing in the system. In the paper, the models that use Petri Nets were considered. These models were used for simulating the execution of tests among system units. Two methods for performing such simulations were evaluated and compared. Recommendations for choosing a more appropriate way were made. Simulation results have revealed minor model deficiencies and possible implementation of mutual testing in complex systems. Improvement of the model was suggested and assessed. A recommendation for increasing the efficiency of system diagnosis based on joint testing was made.

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Complex system, mutual testing, modelling, simulation, petri nets

Короткий адрес: https://sciup.org/15018849

IDR: 15018849   |   DOI: 10.5815/ijigsp.2023.06.07

Список литературы Modeling and Simulating Mutual Testing in Complex Systems by Using Petri Nets

  • Ribbens W. B. Electronic control system diagnosis. In Understanding Automative Electronics, 2017, doi: 10.1016/c2016-0-00011-6.
  • Rentschler M., Kehrer S., Zangl C. P. System self-diagnosis for industrial devices. IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA), pp. 1-8, 2013.
  • Zhu M., Li J., Wang W., Chen D. Self-detection and self-diagnosis methods for sensors in intelligent integrated sensing system. In IEEE Sensors Journal, 2021, doi: 10.1109/JSEN.2021.3090990.
  • Morris A. S., Langari R. Measurement and Instrumentation Theory and Application, Elsevier Science, 2015, 726 pages.
  • Preas B. Smart matter systems, an introduction through examples. Proc. Of the International Symposium on physical design, ISPD’14, pp. 131-132, 2014.
  • Mashkov V.A., Barabash O.V. Self-testing of multimodule systems based on optimal check-connection structures. Engineering Simulation, 13(3), 479-492 (1996).
  • Mashkov V.A., Mashkov O.A. Interpretation of diagnosis problem of system level self-diagnosis. Mathemetical Modeling and Computing, 2(1), pp. 71-76 (2015).
  • Preparata T., Metze G., Chien R. On the connection assignment problem of diagnosable system. IEEE Transactions on Electronic Computers. EC-16, n.12, 848–854 (1967).
  • M. Barborak M., Malek M., Duhbura A. The Consensus Problem in Fault Tolerant Computing. ACM Computing Surveys, vol. 25, No. 2, (1993).
  • Laforge L., Korver K.F. Mutual test and diagnosis: architectures and algorithms for spacecraft avionics. Proceedings of IEEE Aerospace Conference. Vol. 5, 295-306 (2000).
  • Petri A. Kommunikation mit Automaten. Bonn: Institute fur Instrumentelle Mathematik. Schriffen des IIM Nr. 3, 19622. Also, English translation „Communication with Automata“, New York: Griffiss Air Forth Base, Tech., Rep. RADC-TR-65-377, Vol. 1, Suppl. 1, 1966.
  • Peterson J. L. Petri Net Theory and the Modeling of Systems. Prentice Hall, New York, 1981, 290 pages.
  • Billington J., Diaz M., Rozenberg C. Application of Petri nets to communication networks. Advances in Petri Nets, LNCS, 1, 1999, 314 pages.
  • Mashkov V., Barilla J., Simr P. Applying Petri Nets to modeling of many-core processor self-testing when tests are performed randomly. Journal of Electronic Testing, Vol.29, No.1, 25-34 (2013).
  • Bobbio A. System modeling with Petri Nets. In: A.G. Colombo and A. Saiz de Bustamante (eds.). System Reliability Assessment, Kluwer p.c., 102-143 (1990).
  • Sahner R.A., Trivedi K.S. Reliability modeling using SHARPE. IEEE Trans. Reliab. R-36(2), 186-193 (1987).
  • Reddy, V. N., Mavrovouniotis, M. L.: Petri net representation in metabolic pathways. Proc. Int. Conf. Intell. Syst. Mol. Biol. vol. 1, pp. 328-336. (1993)
  • Mashkov V., Barilla J., Simr P., Bicanek J. Applying petri nets to coalition formation modeling. Advances in Intelligent Systems and Computing, 442, pp. 83-97 (2016).
  • T. Preparata, G. Metze, R. Chien. On the connection assignment problem of diagnosable system. IEEE Transaction on Electronic Computers. Vol. EC-16, No. 12, pp. 848-854, 1967.
  • M. L. Blount. Probabilistic treatment of diagnosis in digital systems. In 7th IEEE Int. Symp. On Fault-Tolerant Computing, pp. 72-77, 1977.
  • T. Barsi, T. Grandoni, P. Maestrini. A theory of diagnosis of multiprocessor systems. In Proc. of the 7th Annual Symposium on Computer Architecture, pp. 31-36, 1980.
  • M. Barborak, M. Malek, A.T. Dahbura. The consensus problem in fault-tolerant computing. ACM Computing Surveys. Vol. 25, No. 2, pp. 171-220, 1993.
  • A.K. Somani. System level diagnosis and implications in current context. Chapter on dependable computing systems: paradigms, performance issues, and applications. Edited by Hassan B. Diab and Albert Y. Zomaya. Wiley Series on Paralled and Distributed Computing, 2005 (37 pages).
  • S. Kamal, C.V. Page. Intermittent fault: a model and a detection procedure. IEEE Trans. Comput., Vol. C-23, No. 7, pp. 713-719, 1974.
  • S. Mallela, G. Masson. Diagnosable systems for intermittent faults. IEEE Trans. Comput., Vol. C-27, No. 6, pp. 550-566, 1978.
  • V. Mashkov, J. Fiser, V. Lytvynenko, M. Voronenko. Diagnosis of intermittently faulty units at system level. DATA, 2019, 4(1), 44.
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