Proactive monitoring and management modernization of information systems based on forecasting the level of functional obsolescence
DOI:
https://doi.org/10.17308/sait/1995-5499/2023/2/5-21Keywords:
information system, functional obsolescence, modernization, fuzzy setsAbstract
The purpose of the article is to develop a method for predicting the preferred timing of the modernization of the information system in order to eliminate the causes of its functional obsolescence. Functional obsolescence occurs when the system is unable to meet the changed requirements of users in terms of the composition and quality of the information service functions provided by the system. In order to determine the preferred timing of modernization, it is necessary to have information about trends in the development of user needs, which, in turn, are associated with the possibility of new ideas and technical solutions appearing on the planning horizon of the management of the development of the information system, expanding the requirements for the list and quality of the service functions provided. One of the problems hindering the prediction of the dynamics of functional obsolescence of an information system is the non-stochastic uncertainty of information about parameters (the beginning, the pace, the limit level) of the obsolescence process. Such information can be obtained only from experts in the subject area in the form of approximate (fuzzy) estimates on the axes of time and the degree of obsolescence. The scientific novelty lies in the application of a new mathematical forecasting model of a twice-fuzzy time series within the framework of the proposed method, which allows to obtain two forms of forecast: a direct forecast — in the form of a fuzzy forecast estimate of the degree of obsolescence for given future values of time sections and a reverse forecast — in the form of a fuzzy time forecast estimate of the date of obsolescence. The article contains a description of the features of obtaining and presenting fuzzy expert assessments of changes in the degree of functional obsolescence over time; a description of a model for predicting the process of functional obsolescence and a method for determining the interval assessment of the timing of the onset of functional obsolescence.
References
Lomakin M. I. and Muravyev A. V. (2015) Management of the information system reengineering process based on comprehensive monitoring of moral aging. Measuring equipment. No. 10. P. 16–20.
Shestopalova O. L. (2017) Managing the development of information systems taking into account the monitoring of moral aging. Modern high-tech technologies. No. 6. P. 103–107.
Mironov A. N. (2000) Theoretical foundations and methods of multi-model forecasting of the durability of complex military-technical systems for space purposes. Monograph. Ministry of Defense of the Russian Federation. 430 p.
GOST R 27.203-2012 (2014) Reliability in technology. Obsolescence management. Moscow : Standartinform. 23 p.
Muravyev A. V. and Shestopalova O. L. (2014) Forecasting the moral aging of the information system. Monograph. Moscow. Moskovsky pechatnik. 88 p.
Kononikhin S. A. and Shestopalova O. L. (2011) Features of estimating the residual resource of applied distributed information systems taking into account the factors of moral aging. Information and economic aspects of standardization and technical regulation: Online Journal. No 2. P. 11–23.
Shestopalova O. L. (2021) Forecasting the obsolescence of information collection and processing systems of space complexes by the criterion of the effectiveness of information support. News of higher educational institutions. Instrumentation. Vol. 64, No 2. P. 81–89.
Muravyev A. V. and Shestopalova O. L. (2014) Forecasting the service life of an information system taking into account the moral aging of the element base of technical means. Transport business of Russia. No 6. P. 186–189.
Shestopalova O. L. (2013) Forecasting the moral durability of distributed information systems, taking into account the progressive limitations on the possibility of restoring the resource of the element base. Modern problems of science and education. No 6. 13 p.
Kononikhin S. A. and Shestopalova O. L. (2011) Forecasting the durability of equipment of applied distributed information systems taking into account restrictions on resource recovery. Information and economic aspects of standardization and technical regulation: Internet Journal. No 3. P. 13–21. Available at: http://iea.gostinfo.ru/magazine_02%283%29.html.
Mironov E. A., Klepov A. V. and Shestopalova O. L. (2014) Ensuring the technical and economic efficiency of the operation of a distributed information system [Electronic resource]. Information and economic aspects of standardization and technical regulation: Scientific Online journal. No 5(21). P. 11–19.
Okhtilev M. Yu., Okhtilev P. A., Sokolov B. V. and Yusupov R. M. (2022) Methodological and methodological foundations of proactive life cycle management of complex technical objects. Izvestiya Vuzov. Instrumentation. No 11. P. 781–788.
Akhtyrchenko K. V. and Sorokvasha T. P. (2003) Methods and technologies of IP reengineering. Proceedings of the Institute of System Programming of the Russian Academy of Sciences. Vol. 4. P. 141–162.
Shestopalova O. L. (2019) Forecasting the degree of functional obsolescence of information systems on the basis of extrapolation of fuzzy expert assessments. Izvestia of Higher Educational Institutions. Instrumentation. Vol. 62, No 4. P. 312–319.
Sevastyanov D. A.,. Tsvetkov K. Yu. and Shestopalova O. L. (2016) Modeling of the process of functional moral aging of a telecommunication system based on the extrapolation of fuzzy time series. Proceedings of the III All-Russian Scientific and practical conference “Modern problems of creation and operation of weapons, military and special equipment”, December 14–15, 2016. Vol. 2. St. Petersburg. P. 219–224.
Litvak B. G. (1982) Expert information: Methods of obtaining and analysis. Moscow : Radio and Communications. 184 p.
Pospelov D. A. (1981) Logical-linguistic models in control systems. Moscow : Energoizdat. 232 p.
Pegat A. (2013) Fuzzy modeling and control. Trans. from English. 2nd ed. Moscow : BINOM. Laboratory of Knowledge. 798 p.
Downloads
Published
Issue
Section
License
Условия передачи авторских прав in English
