Semi-Markov Estimation of Dependability of Information System for Critical Use

Authors

  • V. V. Kovtun Vinnytsia National Technical University

DOI:

https://doi.org/10.31649/1997-9266-2019-143-2-61-77

Keywords:

system for critical use, dependability, controlled semi-Markov process, multi-state system, stochastic modeling

Abstract

The information system for critical use (ISCU) can be classified as a complex, extensive information system operating in the software-hardware environment of a network client-server system. To estimate the dependability of the hardware component of the ISCU we can use known, approved, correct methods. At the same time, in order to estimate the dependability of the information component of the system, additional studies are required related to the specific features of the ISCU architecture and its critical use. In particular, an object-oriented description of such indicators of dependability as reliability, recoverability, and structural redundancy are necessary. Also, when modeling it is necessary to take into account the specific interpretation of the concept of a functional state for such a system. Analysis of the results of an information search has shown that the mathematical apparatus of Markov networks turns out to be optimal for the dependability estimation of the ISCU modelling from the standpoint of taking into account the architectural features of the system and the specifics of its functioning. Thus, for the first time, a complex of the controlled semi-markov models describing the dynamics of the functioning information system for critical use was proposed, in which, unlike the existing ones, the system being modeled is considered as a many states system, in which semi-markov description the states described by different distributions agree, which allows to formalize the maximum likelihood estimation function and parameters of the semi-Markov process that describes the life cycle of the ISCU, for possible types of distributions of its states, identify the Markov recovery functions and the semi-Markov transition matrix of this process and formulate expressions for calculating the indicators of the simulated system's dependability. The article synthesizes expressions for calculating the likelihood for uncensored and censored specific segments of semi-Markov processes with one and many trajectories that simulate the life cycle of the ISCU. Expressions for the maximum likelihood estimation and the parameters estimation of the original distribution class, which are basic for certain semi-Markov processes, are synthesized. Expressions are obtained for estimating such integral characteristics of the dependability of the ISCU as reliability, availability, maintainability, failure rate and the average system uptime in the formalism of the semi-Markov models obtained. This article analytically proved the correctness of the obtained estimates of the parameters of a semi-Markov process that simulates the operation of an information system for critical use. An empirical study was conducted in which the proposed methodology for estimating the dependability of efficiency of the ISCU was tested. The results of the study proved, in particular, that an analytical assessment of the reliability of the simulated system approaches the real value of this characteristic with an increase in the interval of observation of the operation of the ISCU, and the confidence interval for the reliability calculated on the basis of the proposed models covers the real value of this characteristic.

Author Biography

V. V. Kovtun, Vinnytsia National Technical University

Cand. Sc. (Eng.), Associate Professor, Associate Professor of the Chair of Computer Control Systems

References

В. В. Ковтун, «Концепція впровадження автоматизованої системи розпізнавання мовця у процес автентифікації для доступу до критичної системи,» Вісник Вінницького політехнічного інституту, Вінниця, № 5, с. 41-52. 2018. https://doi.org/10.31649/1997-9266-2018-140-5-41-52.

V. V. Kovtun et al., “The automated speaker recognition system of critical use,” Proc. SPIE 10808, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2018, 108082V. https://doi.org/ 10.1117/12.2501688.

W. Zamojski, and J. Sugier, Dependability Problems of Complex Information Systems, Heidelberg, Germany: Springer Cham Heidelberg, 2015, P. 194. https://doi.org/10.1007/978-3-319-08964-5.

Mario Tokoro, Open Systems Dependability: Dependability Engineering for Ever-Changing Systems, Second Edition, Boca Raton, USA: CRC Press, 2015, P. 288.

O. V. Bisikalo, V. V. Kovtun, M. S. Yukhimchuk, and I. F. Voytyuk, “Analysis of the automated speaker recognition system of critical use operation results,” Radio Electronics, Computer Science, Control, Zaporizhzhia. №4, pp. 71-84. 2018. https://doi.org/10.15588/1607-3274-2018-4-7.

Krzysztof Kolowrocki, and Joanna Soszynska-Budny, “Introduction to safety analysis of critical infrastructures,” International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, Chengdu, China, 2012, pp. 1-6. https://doi.org/10.1109/ICQR2MSE.2012.6246177.

Barry Boehm, LiGuo Huang, Apurva Jain, and Ray Madachy, “The Nature of Information System Dependability: A Stakeholder/Value Approach” [Online]. Available: http://csse.usc.edu/TECHRPTS/2004/usccse2004-520/usccse2004-520.pdf. Accessed on: February 28, 2019.

Nikola Samec, and Alen Jakupović, “Methods and software for estimation of information system dependability,” 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija, Croatia. 2014, pp. 1281-1285. https://doi.org/10.1109/MIPRO.2014.6859723.

Hwee-Pink Tan, and Austin Zhang, “Real-world large-scale IoT systems for community eldercare: A comparative study on system dependability,” International Conference on Information Networking (ICOIN), Chiang Mai, Thailand, pp. 880-885, 2018. https://doi.org/ 10.1109/ICOIN.2018.8343248.

Yi Qian, David Tipper, Prashant Krishnamurthy, and James Joshi, Information Assurance: Dependability and Security in Networked Systems. San Francisco, USA: Morgan Kaufmann Publishers Inc, p. 576, 2008.

Jacek Mazurkiewicz, “Agent Approach to Network Systems Dependability Analysis in Case of Critical Situations,” Zamojski W., Sugier J. (eds) Dependability Problems of Complex Information Systems. Advances in Intelligent Systems and Computing Springer, Cham, vol. 307, pp. 73-89, 2015. https://doi.org/10.1007/978-3-319-08964-5_5.

Zhibao Mian, Leonardo Bottaci, Yiannis Papadopoulos, Septavera Sharvia, and Nidhal Mahmud, “Model Transformation for Multi-objective Architecture Optimisation of Dependable Systems,” Zamojski W., Sugier J., Eds. Dependability Problems of Complex Information Systems. Advances in Intelligent Systems and Computing, Springer, Cham, vol. 307, pp. 91-110, 2015. https://doi.org/10.1007/978-3-319-08964-5_6.

Li Rui, Yu Tao, and Fang Ming-lun, “Reliability management for information system,” Journal of Shanghai University, vol. 9, iss. 3, pp. 268-274, 2005. https://doi.org/10.1007/s11741-005-0091-1.

Franciszek Grabski, “Semi-Markov Processes: Applications in System Reliability and Maintenance. 1st Edition,” Elsevier, 2014, p. 270. https://doi.org/10.1016/C2013-0-14260-2.

Nikolaos Limnios, “Dependability analysis of semi-Markov systems,” Reliability Engineering and System Safety, Elsevier, Northern Ireland, vol. 55, pp. 203-207, 1999. https://doi.org/10.1016/S0951-8320(96)00121-4.

Vandana Gupta1, and S. Dharmaraja, “Semi-Markov modeling of dependability of VoIP network in the presence ofresource degradation and security attacks,” Reliability Engineering and System Safety, Elsevier, Northern Ireland, vol. 96, pp. 1627-1636, 2011. https://doi.org/10.1016/j.ress.2011.08.003.

Jorge E. Hurtado, and Diego A. Alvarez, “Neural-network-based reliability analysis: a comparative study,” Computer Methods in Applied Mechanics and Engineering, vol. 191, iss. 1-2, pp. 113-132, 2001. https://doi.org/ 10.1016/S0045-7825(01)00248-1.

Chih-Hong Cheng, Chung-Hao Huang, and Georg N ̈uhrenberg, “nn-dependability-kit: Engineering NeuralNetworks for Safety-Critical Systems” [Online]. Available: https://github.com/dependable-ai/nn-dependability-kit. Accessed on: March 05, 2019.

І. І. Горбань, Теорія ймовірностей і математична статистика для наукових працівників та інженерів. Київ: Національна академія наук України, Інститут проблем математичних машин і систем, 2003, 244 c.

Nikolaos Limnios, “Reliability Measures of Semi-Markov Systems with General State Space,” Methodology and Computing in Applied Probability, vol. 14, iss. 4, pp. 895-917. 2012. https://doi.org/10.1007/s11009-011-9211-5.

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Published

2019-04-26

How to Cite

[1]
V. V. Kovtun, “Semi-Markov Estimation of Dependability of Information System for Critical Use”, Вісник ВПІ, no. 2, pp. 61–77, Apr. 2019.

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Information technologies and computer sciences

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