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

Calculation methods of the prognostication of the computer systems state under different volume of a priori information and accuracy of the measurement 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 basic features of the methods. Synthesized methods do not impose any significant limitations on the qualities of the sequence of the change of the forecast parameters (linearity, stationarity, Markov behavior, monotoneness, etc.) and allow to take into account the stochastic peculiarities of the process of functioning of the investigated objects as much as possible. Expressions of the determination of a mean-square extrapolation error are obtained for solving the prognostication problems specifically concerning the state of computer systems under different level of information uncertainty.