International Journal of Intelligent Systems and Applications(IJISA)

ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)

Published By: MECS Press

IJISA Vol.11, No.1, Jan. 2019

Method for Unit Self-Diagnosis at System Level

Full Text (PDF, 1139KB), PP.1-12

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Viktor Mashkov, Volodymyr Lytvynenko

Index Terms

System-level diagnosis;self-diagnosis;intermittent fault;hybrid-fault situations;computer simulation


This paper suggests unconventional approach to system level self-diagnosis. Traditionally, system level self-diagnosis focuses on determining the state of the units which are tested by other system units. In contrast, the suggested approach utilizes the results of tests performed by a system unit to determine its own state. Such diagnosis is in many respects close to self-testing, since a unit evaluates its own state, which is inherent in self-testing. However, as distinct from self-testing, in the suggested approach a unit evaluates it on the basis of tests that it does not performs on itself, but on other system units. The paper considers different diagnosis models with various testing assignments and diferent faulty assumptions including permanent and intermittent faults, and hybrid- fault situations. The diagnosis algorithm for identifying the unit’s state has been developed, and correctness of the algorithm has been verified by computer simulation experiments.

Cite This Paper

Viktor Mashkov, Volodymyr Lytvynenko, "Method for Unit Self-Diagnosis at System Level", International Journal of Intelligent Systems and Applications(IJISA), Vol.11, No.1, pp.1-12, 2019. DOI: 10.5815/ijisa.2019.01.01


[1]F. Preparata, G. Metze, R. Chien, “On the connection assignment problem of diagnosable systems”, IEEE Transactions on Electronic Computers (EC-16), 6 (Dec.), pp. 848-854, 1967.

[2]V. Mashkov, O. Barabash, “Self-checking of modular systems under random performance of elementary checks”, Engineering Simulation, Vol.12, pp. 433-445, 1995.

[3]V. Mashkov, O. Barabash, “Self-testing of multimodule systems based on optimal check-connection structures”, Engineering Simulation, Vol.13, pp. 479-492, 1996.

[4]V. Mashkov, “Selected problems of system level self-diagnosis”, Lviv, Ukrainian Academic Press, 2011, ISBN 978-966-322-365-0.

[5]M. Malek, “A comparison connection assignment for diagnosis of multiprocessor systems”, in Proceedings of the 7th Annual Symposium on Computer Architecture, pp. 31-36, 1980.

[6]M. Ding, D. Chen, K. Xing, X. Cheng, “Localized fault-tolerant event boundary detection in sensor networks”, IEEE Infocom, pp. 902-913, 2005.

[7]A. Russoniello, E. Gamess, "Evaluation of Different Routing Protocols for Mobile AdHoc Networks in Scenarios with High-Speed Mobility", International Journal of Computer Network and Information Security (IJCNIS), Vol.10, No.10, pp.46-52, 2018.

[8]M. N. Riaz, "Clustering Algorithms of Wireless Sensor Networks: A Survey", International Journal of Wireless and Microwave Technologies (IJWMT), Vol.8, No.4, pp. 40-53, 2018.

[9]N. V. Dinh, N. X. Thao, “Some Measures of Picture Fuzzy Sets and Their Application in Multi-attribute Decision Making”, I.J. Mathematical Sciences and Computing (IJMSC), Vol.4, No.3, pp. 23-41, 2018.

[10]N. Meskin, K.Khorasaniy, “Fault detection and isolation of discrete-time Markovian jump linear systems with application to a network of multiagent systems having imperfect communication channels”, Automatica, 45(9), pp. 2032-2040, 2009.

[11]R. Micalizio, P. Torasso, G. Torta, “On-line monitoring and diagnosis of multi-agent systems: A model based approach”, 16th European Conference on Artificial Intelligence (ECAI), Valencia, Spain, Vol. 16, p. 848, 2004.

[12]C. Wang, W. Shang, D. Sun, “Monitoring malfunction in multirobot formation with a neural network detector”. Journal of Systems and Control Engineering, Vol. 225, pp. 1163-1172, 2011.

[13]F. Barsi, F. Grandoni, P.Maestrini, “A theory of diagnosability of digital systems”, IEEE Transactions on Computers, Vol. C-25, No.6, pp.585-593, 1976.

[14]N. Meskin, K. Khorasani, C. A. Rabbath, “A hybrid fault detection and isolation strategy for a network of unmanned vehicles in presence of large environmental disturbances”, IEEE Transactions on Control Systems Technology, 18(6), pp. 1422-1429, 2010.

[15]G. Cueva-Fernandez, J. Pascual Espada, V. Garcia-Diay, R. Gonzalez-Crespo, “Fuzzy decision method to improve the information exchange in a vehicle sensor tracking system”, Applied Soft Computing, Vol.35, pp. 708-716, 2015. 

[16]N. Lchevin, C. A. Rabbath, E. Earon, “Towards decentralized fault detection in uav formations”, Control Conference, ACC07, New York City, USA, pp. 5759-5764, 2007.

[17]A.Bobbio, “System modelling with Petri Nets”, In: A.G. Colombo and A. Saiz de Bustamante (eds.). System Reliability Assessment, pp.102-143, 1990.

[18]A. Apostolakis, D. Gizopoulos, M. Psarakis, A. M. Paschalis, “Software-Based Self-Testing of Symmetric Shared-Memory Multiprocessors”, IEEE Transactions on Computers, Vol. 58, No. 12, pp.1682-1694, 2009.

[19]V. Mashkov, “New approach to system level self-diagnosis”, in Proceedings of IEEE 11th International Conference on Computer and Information Technology, CIT2011, Cyprus, pp.579-584, 2011.

[20]M. Elhadef, A. Boukerche, H.Elkadiki, “Performance analysis of a distributed comparison-based self-diagnosis protocol for wireless ad hoc networks”, in Proceedings of the 9th ACM International Symposium on Modeling Analysis and Simulation of Wireless and Mobile Systems, pp.165-172, 2006.

[21]S. Jangale, D.Hadsul, “Detection of faulty sensor nodes in wireless sensor network”, Computer technology and Applications, Vol.4, No.1, pp. 150-154, 2009.

[22]M. H. Lee, Y. H. Choi, “Fault   detection   on   wireless   sensor networks”, Computer Communications, Vol. 31, 2008.

[23]L. Albini,  J. Duarte,  R. Ziwich, “A generalized model for distributed comparison-based system-level diagnosis”, J. Brazi, Comput. Soc., Vol. 10, No. 3, pp. 44-56, 2005.

[24]J. Chen, S. Kher, A.Somani, “Distributed fault detection of wireless  sensor network”, in Proceedings of the International Conference on Mobile Computing and Networking, New York, USA, pp. 65-72, 2006.

[25]S. Chessa, P.Santi, “Comparison-based system-level fault diagnosis in ad hoc network”, in 20th Symp. Reliable Distributed Systems, pp. 257-266, 2001.

[26]J. Xu., “The t/(n-1) diagnosability and its application to fault tolerance”, Technical report, No. 340, University of Newcastle upon Tyne, 1991.

[27]V. Mashkov, J. Pokorny, “Scheme for comparing results of diverse software versions”, in Proc. of ICSOFT Conference, Barcelona, Spain, pp.341- 344, 2007.

[28]M. J. Daigle, X. D. Koutsoukos, G. Biswas, “Distributed diagnosis in formations of mobile robots”, IEEE Transactions on Robotics, Vol.23, No.2, pp. 353-369, 2007.

[29]P. M. Khilar, “Performance analysis of distributed intermittent fault diagnosis in wireless networks using clustering”, in Proceedings of 5th International Conference on Industrial and Information Systems, ICIIS, pp. 13-18, 2010.

[30]B. Krishnamachari, S.Iyengar, “Distributed Bayesian algorithms for fault-tolerant event region detection in wireless sensor networks”, IEEE Transaction on Computers, Vol.53, No.3, pp. 241-250, 2004.

[31]X. Luo, M. Dong, Y. Huang, “On distributed fault-tolerant detection in wireless sensor networks”, IEEE Transactions on Computers, Vol.55, No.1, pp. 58-70, 2006.

[32]A. Auddy, S. Mukhopadhyay, "Modelling Online Admission System: A MultiAgent Based Approach", International Journal of Modern Education and Computer Science (IJMECS), Vol.6, No.5, pp. 26-32, 2014. 

[33]P. Jiang, “A new method for fault detection in wireless sensor networks”, in Proceeding of ISSN 1424-8220, Hangzhou Dianzi Unversity, 2009.

[34]S. Mallela, G. Masson, “Diagnosable systems for intermittent faults”, IEEE Transactions on Computers, Vol.C-27, 6 (June), pp. 560-566, 1978.

[35]L. Qin, X. He, D. H. Zhou, “A survey of fault diagnosis for swarm systems”. Systems Science and Control Engineering: An Open Access Journal, Vol.2, pp. 13-23, 2014.

[36]M. Dhar, H.K. Baruah, “Theory of Fuzzy Sets: An Overview”, I.J. Information Engineering and Electronic Business (IJIEEB), Vol.5, No.3, pp.22-33, 2013. 

[37]S. Kamal, C. V. Page, “Intermittent faults: A model and a detection procedure”, IEEE Transactions on Computers, Vol.23, Iss.7, pp. 713-719, 1974.

[38]J. Collet, P. Zajac, M. Psarakis, D. Gizopoulos, “Chip self-organization and fault-tolerance in massively defective multicore arrays”, IEEE Transactions on Dependable and Secure Computing, Vol.8, No.2, pp.207-217, 2011.

[39]V. Mashkov, J. Barilla, P. Simr, “Applying Petri Nets to Modeling of Many-core Processor Self-testing when Tests are Performed Randomly”, Journal of Electronic Testing, Vol.29, No.1, pp.25-34, 2013.

[40]PNsimulator. Available at

[41]A. Barua, K. Khorasani, “Intelligent model-based hierarchical fault diagnosis for satellite formations”. IEEE international conference on Systems, Man and Cybernetics, ISIC, Montreal, Quebec, Canada, 2007, pp. 3191-3196. 

[42]V. Mashkov,  “Task  allocation among agents of restricted alliance”, in  Proc.  of IASTED ISC2005 Conference, Cambridge, MA, USA, pp.13-18, 2005.

[43]V. Mashkov, “Restricted alliance and coalition formation”, Proc. of IEEE/WIC/ACM International Conference on Intelligent Agent Technology, China, pp. 329-332, 2004.