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Editor-in-Chief
Nikiforov
Vladimir O.
D.Sc., Prof.
Partners
doi: 10.17586/2226-1494-2020-20-5-677-682
HIERARCHICAL DIAGNOSTIC MODEL SYNTHESIS FOR DATAFLOW REAL-TIME COMPUTING SYSTEM
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Article in Russian
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Abstract
For citation:
Lukoyanov E.V., Gruzlikov A.M. Hierarchical diagnostic model synthesis for dataflow real-time computing system. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2020, vol. 20, no. 5, pp. 677–682 (in Russian). doi: 10.17586/2226-1494-2020-20-5-677-682
Abstract
Subject of Research. The paper considers design issues for diagnostic tools of fault detection in addressing information exchanges between software modules for real-time dataflow computing systems. Despite the decomposition of the design processes in such systems, the issues of diagnostics and fault tolerance remain relevant for each hierarchy level. Method. The proposed synthesis procedures for the hierarchical model of a dataflow computing system are the result of the test diagnostics method development based on the parallel model application. Main Results. The paper presents a brief description of the test diagnostics method based on the parallel model. An algorithm for hierarchical diagnostics model synthesis is developed. The model minimizes the amount of diagnostic data transmitted through the exchange channels, reducing the redundancy level introduced into the system and thereby increasing the level of reliability. Practical Relevance. The developed hierarchical model reduces significantly the design time for diagnostic tools as a result of reducing the required number of diagnostic modules included in it.
Keywords: parallel model, dataflow computing system, test diagnosis, periodical non-stationary dynamic systems
Acknowledgements. This work was supported by the project No. 19-08-00052 of the Russian Foundation for Basic Research, Russian Federation
References
Acknowledgements. This work was supported by the project No. 19-08-00052 of the Russian Foundation for Basic Research, Russian Federation
References
1. Isermann R. Fault-Diagnosis Applications: Model-Based Condition Monitoring: Actuators, Drives, Machinery, Plants, Sensors, and Fault-Tolerant Systems. Springer Science & Business Media, 2011, XVI, 354 p. doi: 10.1007/978-3-642-12767-0
2. Issues of Fault Diagnosis for Dynamic Systems. Ed. by R.J. Patton, P.M. Frank, R.N. Clark. Springer Science & Business Media, 2000, 597 p. doi: 10.1007/978-1-4471-3644-6
3. Kolesov N.V., Tolmacheva M.V., Yukhta P.V. Real-Time Systems. Planning, Analysis, Diagnostics. St. Petersburg, Concern CSRI Elektropribor, 180 p. (in Russian)
4. Gruzlikov A.M., Kolesov N.V., Lukoyanov E.V. Test-based diagnosis of faults in data exchange addressing in computer systems using parallel model. Journal of Computer and Systems Sciences International, 2018, vol. 57, no. 3, pp. 420–433. doi: 10.1134/S1064230718030024
5. Burdonov I.B., Kosachev A.S., Kuliamin V.V. Compliance Theory for Lock and Crash Systems. Moscow, Fizmatlit Publ., 2008, 412 p. (in Russian)
6. Burdonov I.B., Kossatchev A.S., Kulyamin V.V. Application of finite automatons for program testing. Programming and Computer Software, 2000, vol. 26, no. 2, pp. 61–73. doi: 10.1007/BF02759192
7. Rivkin B.S. Russia’s first integrated navigation systems for commercial vessels. Gyroscopy and Navigation, 2019, vol. 10, no. 1, pp. 35–40. doi: 10.1134/S207510871901005X
8. Gruzlikov A.M., Kolesov N.V. Discrete-event diagnostic model for a distributed computational system. Independent chains. Automation and Remote Control, 2016, vol. 77, no. 10, pp. 1805–1817. doi: 10.1134/S0005117916100076
9. Introduction to Discrete Event Systems. Ed. by C.G. Cassandras, S. Lafortune. 2nd ed. New York, Springer, 2008, 770 p. doi: 10.1007/978-0-387-68612-7
10. Zaytoon J., Lafortune S. Overview of fault diagnosis methods for Discrete Event Systems. Annual Reviews in Control, 2013, vol. 37, no. 2, pp. 308–320. doi: 10.1016/j.arcontrol.2013.09.009
11. Cormen Th.H., Leiserson Ch.E., Rivest R.L., Stein C. Introduction to Algorithms. McGraw-Hill, 2003, 1056 p.