METHOD OF PRESENTING THE PROBABILISTIC INDICATOR OF FUNCTIONAL STABILITY OF THE INFORMATION SYSTEM AS A FUNCTION OF TIME - BARABASH, OLEG; SVYNCHUK, OLGA; MAKARCHUK, ANDRIY (Herald of Khmelnytskyi National University. Technical sciences, 2024)
Information systems are increasingly becoming a vital tool for solving various tasks. Consequently, both theoretical and practical challenges arise related to the design of information systems, their operation, and the diagnosis of their components, among other aspects. Some of these challenges have already been partially resolved; however, in real-world conditions, these tasks often need to be generalized in such a way that allows the characteristics of information systems to be studied in real time. One of the most important characteristics that should ideally be studied in real time, or at the very least predicted for the given information system, is its functional stability. Many indicators developed to mathematically formalize functional stability assume the absence of dynamic changes in the structure of the information system in question, thus limiting their applicability to assessing functional stability only at a specific moment in time. This issue is particularly common with structural indicators due to their specific mathematical formulation. Therefore, there is a need to develop certain generalizations of these indicators that would allow for the prediction of changes in their values over time. One of the functional stability indicators of information systems that can be relatively easily generalized to account for changes over time is the so-called probability of connectivity. The idea behind this indicator is to calculate the probability of information transmission between a selected pair of machines. This paper attempts to make a generalization that would allow the probability of connectivity to be considered as a function of time, and as a result, predict how this probability will change over time. Additionally, certain properties of the introduced parameters that arise from this generalization are explored, and an estimate of their maximum value is established based on the duration of the information system’s operation.