Mathematical model of reliability of information processing computer appliances for real-time control systems
Автор: A. V. Aab, P. V. Galushin, A. V. Popova, V. A. Terskov
Журнал: Siberian Aerospace Journal @vestnik-sibsau-en
Рубрика: Informatics, computer technology and management
Статья в выпуске: 3 vol.21, 2020 года.
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One of the main characteristics of computer appliances for processing real-time information is reliability. The reliability of software is understood as the property of this software to perform specified functions, maintaining its characteristics within the established limits under certain operating conditions. Software reliability is determined by its reliability and recoverability. Reliability of software is a property to maintain its performance when using it for processing information in the information system. The reliability of the software is estimated by the probability of its operation without failures under certain environmental conditions during a given observation period. The development of real-time systems requires a large amount of resources for design and testing. One of the solutions to this problem is mathematical modeling of computer appliances. This allows more flexible design of real-time systems with the specified reliability, taking into account the limitations on price and development time, and also opens the possibility of more flexible optimization of computer appliances for real-time control systems. To develop a mathematical model of the reliability of computer appliance for real-time systems, it is necessary to take into account the provision of a given level of reliability, with reasonable development costs. There are many methods for improving software reliability, but the most promising and effective methods are redundancy, which is achieved using N-version programming. To increase the reliability of the hardware of the computer appliance, it is also necessary to use redundancy and redundancy, which includes multiprocessor and provision of different buses and independent RAM. This paper discusses existing approaches to improving the reliability of hardware and software, proposes a model of reliability of a computer appliance, which is understood as the product of the probability of failure-free operation of hardware and the probability of error-free operation of software. In addition, new formulas are proposed for the steady state probabilities of the hardware states of a multiprocessor computer appliance with heterogeneous processors, which give the same result as the existing ones, but require fewer computations. The paper concludes with a question about the possibility of optimizing the reliability of computer appliances based on the developed model, and indicates optimization methods that can be used to solve this problem.
Reliability, software reliability, real-time systems, mathematical model, multiversion programming.
Короткий адрес: https://sciup.org/148321748
IDR: 148321748 | DOI: 10.31772/2587-6066-2020-21-3-296-302
Список литературы Mathematical model of reliability of information processing computer appliances for real-time control systems
- Buttazzo G. Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications. New York, NY, Springer, 2011. XVI+524 p.
- Vasil'ev V. A., Legkov K. E., Levko I. V. [The real-time systems and applications]. Informaciya i kosmos. 2016, № 3, P. 68–70 (In Russ.).
- CHerkesov G. N. Nadezhnost' apparatnoprogrammnyh kompleksov [Reliability of the computer appliances]. Spb., Piter Publ., 2005, 479 p.
- Lipaev V. V. Ekonomika proizvodstva programmnyh produktov [The economics of the software engineering]. Moscow, SINTEG Publ., 2011, 358 p.
- Zatuliveter Yu. S., Fishchenko E. A., Hodakovskij I. A. [The software methods for improving the reliability of structurally complex distributed computing and control processes]. Nadezhnost'. 2009, No. 1, P. 42–49 (In Russ.).
- Avizienis A. The N-Version Approach to Fault-Tolerant Software. IEEE Trans. Soft. Eng. 1985, Vol. SE-11 (12), P. 1511–1517.
- Kukartsev V. V., Sheenok D. A. [Optimization of the software architecture of logistics information systems]. Logisticheskie sistemy v global'noj ekonomike. 2013, No. 3, P. 138–145 (In Russ.).
- Antamoshkin O. A., Degterev A. S., Rusakov M. A. et al. [The analysis of the reliability of computer appliances]. Uspekhi sovremennogo estestvoznaniya. 2005, No. 6, P. 44–45 (In Russ.).
- Efimov S. N., Terskov V. A. Rekonfiguriruemye vychislitel'nye sistemy obrabotki informacii i upravleniya [The reconfigurable computing systems of information processing and control]. – Krasnoyarsk, KrIZHT IrGUPS Publ., 2013, 249 p.
- Efimov S. N., Tyapkin V. N., Dmitriev D. D. et al. Methods of assessing the characteristics of the multiprocessor computer system adaptation unit. ZHurnal Sibirskogo federal'nogo universiteta. Seriya: Matematika i fizika. 2016, Vol. 9, No. 3, P. 288–295 (In Russ.).
- Graham R. L., Knuth D. E., Patashnik O. Concrete Mathematics – A foundation for computer science. Reading, MA, USA, Addison-Wesley Professional, 1994, 657 p.
- Ventcel' E. S., Ovcharov L. A. Teoriya veroyatnostej i eyo inzhenernye prilozheniya [Probability theory and its engineering applications]. Moscow, Vysshaya shkola Publ., 2000, 480 p.
- Goldberg D. E. Genetic algorithms in search, optimization, and machine learning. Reading, MA, Addison-Wesley, 1989, 372 p.
- Vorozheikin F. Yu., Gonchan T. N., Panfilov I. A. at al. Modified Probabilistic Genetic Algorithm for the Solution of Complex Constrained Optimization Problems. Vestnik SibSAU. 2009. No. 5 (26), Р. 31–36.
- Galushin P. V. [Design and evaluation of asymptotic probabilistic genetic algorithm]. Zhurnal Sibirskogo federal'nogo universiteta. Seriya: Matematika i fizika. 2012, No. 1(5), P. 49–56 (In Russ.).
- Kovalev I. V., Solov'ev E. V., Kovalev D. I. et al. [Application of particle swarm optimization to design of N-version software composition]. Pribory i sistemy. Upravlenie, kontrol', diagnostika. 2013, No. 3, P. 1–6 (In Russ.).
- Semenkin E., Semenkina M. Stochastic Models and Optimization Algorithms for Decision Support in Spacecraft Control Systems Preliminary Design. Informatics in Control, Automation and Robotics, Lecture Notes in Electrical Engineering. 2014, Vol. 283, P. 51–65.
- Semenkin E., Semenkina M. Self-Configuring Genetic Programming Algorithm with Modified Uniform Crossover Operator. Proceedings of the IEEE Congress on Evolutionary Computation. June 10–15, 2012.
