THE STATES’ FINAL PROBABILITIES ANALYTICAL DESCRIPTION IN AN INCOMPLETELY ACCESSIBLE QUEUING SYSTEM WITH REFUSALS AND WITH INPUT FLOW OF REQUIREMENTS’ GROUPS

Abstract

Context. The basis for the creation and management of real queuing systems (QS) is the ability to predict their effectiveness. For the general case of such systems with refusals, with limited approachability of service devices and with a random composition of group requirements in the input flow, the prediction of their performance remains an unsolved problem.
Objective. The research has the aim to find an analytical representation for final probabilities in the above-mentioned case of Markov QS, which allows us to predict the efficiency of its operation depending on the values of the parameters in its structure and control.
Method. For the above-mentioned types of QS, the state probabilities can be described by a system of Kolmogorov’s differential equations, which for the stationary case is transformed into a homogeneous system of linearly dependent algebraic equations. For real QS in communication systems, the number of equations can be estimated by the degree set and amount to several thousand, which gives rise to the problem of their recording and numerical solution for a specific set of operating conditions parameters values. The predictive value of such a solution does not exceed the probability of guessing the numerical values of the QS operating conditions parameters set and for parameters with a continuous value, for example, for random time intervals between requests, is zero.
The method used is based on the analytical transition to the description of QS states groups with the same number of occupied devices. At the same time, the desire to obtain the final probabilities of states in a form close to the Erlang formulas remains. The influence of the above-mentioned QS properties can be localized in individual recurrent functions that multiplicatively distort Erlang formulas.
Results. For the above-mentioned types of QS, analytical calculation formulas for estimating the QS states final probabilities have been found for the first time, which makes it possible to predict the values of all known indicators of system efficiency. In this case, the deformation functions of the states groups’ probability distribution in QS have a recurrent form, which is convenient both for finding their analytical expressions and for performing numerical calculations.
When the parameters of the QS operating conditions degenerate, the resulting description automatically turns into a description of one of known QS with failures, up to the Erlang QS.
Conclusions. The analytical calculation expressions found for the final probabilities of the above-mentioned QS turned out to be applicable to all types of Markov QS with failures, which was confirmed by the results of a numerical experiment. As a result, it became possible to practically apply the obtained analytical description of the considered QS for operational assessments of developed and existing QS effectiveness in the possible range of their operating conditions.