МЕТОДЫ ОБРАБОТКИ ИЗОБРАЖЕНИЙ
РАСПОЗНАВАНИЕ ОБРАЗОВ
МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ
G. P. Akimova, A. V. Solovyev, I. A. Tarkhanov Modeling the Reliability of Distributed Information Systems
G. P. Akimova, A. V. Solovyev, I. A. Tarkhanov Modeling the Reliability of Distributed Information Systems

Abstract.

This article is intended to create a methodology for modeling the reliability of large geographically distributed information systems. In most projects, in which it is required to quantify the reliability of certain information systems, traditionally rely on the reliability of servers and other equipment. However, a large, geographically distributed system is a combination of software and hardware that interact with each other, as well as service personnel that influence the system. Failure of critical components and components due to technical failure or the influence of the human factor can lead to the inoperability of the entire system. Under these conditions, it is important to present the information system as a whole, and not as a set of independent hardware and software. It is best to present the system as a whole helps charting reliability. Methodologies for constructing a reliability scheme and conducting a reliability assessment using this scheme use various reliability indicators and this article is devoted.

Keywords:

digital economy, long-term preservation, big data, distributed registries, reliability

PP. 79-86.

DOI 10.14357/20718632190307

References

1. Pitt L. F., Watson R. T., Kavan C. B. Service quality: a measure of information systems effectiveness // MIS quarterly, 1995. P. 173-187.
2. Waseem A., Wu Y.W. A survey on reliability in distributed systems» // Journal of Computer and System Sciences 2013. No. 79.8. P. 1243-1255.
3. Boudreau M. C., Gefen D., Straub, D. W. Validation in information systems research: a state-of-the-art assessment.// MIS quarterly. 2001. P. 1-16.
4. Kapoor P.K., Pham H., Gupta A., Jha P.C. Software reliability assessment with OR applications. // Springer, London, 2011.
5. Cormen T. H., Leiserson C. E., Rivest R. L., Stein C. Introduction to Algorithms. // Third Edition. MIT Press. ISBN 0-262-03384-4. Section 23.2: The algorithms of Kruskal and Prim, 2009. P. 631–663.
6. A.V.Soloviev, Concept «Umnyj gorod Skolkovo» for Skolkovo innovation center and set of measures for its implementation. Vol 3. Logiko-matematicheskaja model' «Umnogo goroda»: research report. ISA RAN. 2012, 141 p.
7. A.V. Soloviev, E.Y. Komleva, “Metodicheskoe obespechenie nadezhnosti v oblasti hranenija jelektronnyh dokumentov”, Proceedings of the XXIII International Conference "Documentation in the Information Society: Archival Studies and Documentation in the Modern World", Rosarchive, 2017, pp. 321-331.
8. G.P. Akimova, A.V.Solovyev, I.A. Tarkhanov. Reliability Assessment Method for Geographically Distributed Information Systems // The IEEE 12th International Conference on Application of Information and Communication Technologies / AICT 2018 (17-19 Oct. 2018, Almaty, Kazakhstan), IEEE, 2018, P.188-191.
9. G.P. Akimova, E.V. Pashkina, A.V. Soloviev. “Analiz ocenki jeffektivnosti ierarhicheskoj territorial'noraspredelennoj informacionnoj sistemy na primere GAS “Vybory“, Proceedings of the Institute of System Analysis of the Russian Academy of Sciences, vol. 58, pp. 25- 38, 2010.
10. Svobodova L. Reliability issues in distributed information processing systems. // Dig. Papers FTCS-9: 9th Annu. Symp. Fault-Tolerant Computing. 1979.
11. Delone W. H., McLean E. R. The DeLone and McLean model of information systems success: a ten-year update. // Journal of management information systems. 2003. No. 19(4). P. 9-30.
12. Goševa-Popstojanova K., Kishor S. T. Architecturebased approach to reliability assessment of software systems. // Performance Evaluation. 2001. No. 45.2-3. P. 179-204.
13. Krishnan R., Peters J., Padman R., Kaplan D. On data reliability assessment in accounting information systems. // Information Systems Research. 2005. No. 16(3). P. 307-326.
14. Choudhary A., Baghel A.S., Sangwan O.P. Parameter Estimation of Software Reliability Model Using Firefly Optimization. // Data Engineering and Intelligent Computing.  Springer. Singapore. 2018. P. 407-415.
15. Zheng Z. Semi-markov models of composite web services for their performance, reliability and bottlenecks. // IEEE Transactions on Services Computing. 2017. No. 10.3. P. 448-460.
16. Xu J., Yu D., Hu Q., Xie M. A reliability assessment approach for systems with heterogeneous component information // Quality Engineering. 18.12.2017. P.1-11 https://doi.org/10.1080/08982112.2017.1402935.
 

 

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