Calculation Methods of the Prognostication of the Computer Systems State under Different Level of Information Uncertainty

Abstract

Calculation methods of the prognostication of the computer systems state under different volume of a priori information and accuracy of the meas-urement of controlled parameters (under absence and presence of measurement errors) are obtained in the work. Canonical expansions of random sequences of the indices characterizing the state of the investigated systems considered as ba-sic features of the methods. Synthesized methods do not impose any significant limitations on the qualities of the sequence of the change of the forecast pa-rameters (linearity, stationarity, Markov behavior, monotoneness, etc.) and al-low to take into account the stochastic peculiarities of the process of function-ing of the investigated objects as much as possible. Expressions of the determi-nation of a mean-square extrapolation error are obtained for solving the prog-nostication problems specifically concerning the state of computer systems un-der different level of information uncertainty.