Informatics and Applications
2015, Volume 9, Issue 1, pp 98-105
BAYESIAN RECURRENT MODEL OF RELIABILITY GROWTH:
BETA-UNIFORM DISTRIBUTION OF PARAMETERS
- Iu. V. Zhavoronkova
- A. A. Kudryavtsev
- S. Ya. Shorgin
Abstract
Forecasting reliability of complex modifiable information systems is one of the topical problems of the
mass service theory nowadays. Any first established complex system designed for processing or transmission of
information flows, as a rule, does not possess the required reliability. Such systems are subject to modifications
during development, testing, and regular functioning. The purpose of such modifications is to increase reliability
of information systems. In this connection, there is a necessity to formalize the concept of reliability of modifiable
information systems and to develop methods and algorithms of estimation and forecasting of various reliability
characteristics. One approach to determine system reliability is to compute the probability that the signal fed to
the input of the system at a given point of time will be reacted to correctly by the system. The article considers
the exponential recurrent growth model of reliability, in which the probability of system reliability is represented
as a linear combination of “defectiveness” and “efficiency” parameters of tools correcting the deficiencies in the
system. It is assumed that the researcher does not have exact information about the system under study and is only
familiar with the characteristics of the class from which this system is taken. In the framework of the Bayesian
approach, it is assumed that one of the indicators of “defectiveness” and “efficiency” has the beta-distribution and
the other one has the uniform distribution. Average marginal system reliability is calculated. Numerical results for
model examples are obtained.
[+] References (5)
- Gnedenko, B. V., and V. Yu. Korolev. 1996. Random summation:
Limit theorems and applications. Boca Raton, FL:
CRC Press, 1996. 288 p.
- Korolev, V. Yu., and I.A. Sokolov. 2006. Osnovy matematicheskoy
teorii nadezhnosti modifitsiruemykh system [Fundamentals
of mathematical theory of modified systems
reliability]. Moscow.: IPI RAN, 2006. 108 p.
- Kudryavtsev, A.A., I. A. Sokolov, and S. Ya. Shorgin.
2013. Bayesovskaya rekurrentnaya model’ rosta nadezhnosti:
Ravnomernoe raspredelenie parametrov [Bayesian
recurrentmodel of reliability growth: Uniformdistribution
of parameters]. Informatika i ee Primeneniya — Inform.
Appl. 7(2):55–59.
- Zhavoronkova, Iu. V., A.A. Kudryavtsev, and S. Ya. Shorgin.
2013. Bayesovskaya rekurrentnaya model’ rosta
nadezhnosti: Beta-raspredelenie parametrov [Bayesian recurrent
model of reliability growth: Beta-distribution of
parameters]. Informatika i ee Primeneniya — Inform. Appl.
8(2):48–54.
- Gradshteyn, I. S., and I.M. Ryzhik. 1971. Tablitsy integralov,
summ, ryadov i proizvedeniy [Tables of integrals,
sums, series, and products].Moscow: Nauka. 1108 p.
[+] About this article
Title
BAYESIAN RECURRENT MODEL OF RELIABILITY GROWTH:
BETA-UNIFORM DISTRIBUTION OF PARAMETERS
Journal
Informatics and Applications
2015, Volume 9, Issue 1, pp 98-105
Cover Date
2014-10-30
DOI
10.14357/19922264150109
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
modifiable information systems; theory of reliability; Bayesian approach; beta-distribution; uniform
distribution
Authors
Iu. V. Zhavoronkova  , A. A. Kudryavtsev  , and S. Ya. Shorgin 
Author Affiliations
Sputnik Ltd., 8/2 Prishvina Str., Moscow 127549, Russian Federation
Faculty of Computational Mathematics and Cybernetics, M.V. Lomonosov Moscow State University, 1-52
Leninskiye Gory, GSP-1,Moscow 119991, Russian Federation
Institute of Informatics Problems, Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian
Federation
|