Model of Verification of Distributed Storage Systems

The correctness and stability of distributed data storage systems is one of the key and, at the same time, special conditions for the overall performance of a wide variety of domain-oriented networked computer systems. In this regard, information-dynamic aspects of ensuring the reliability of the functioning of distributed data storage systems based on analysis, verification and prediction, including statistical ones, of their states and behavior are of interest. The present paper discusses the development of a verification model for distributed data storage systems based on a state diagram (machine), statistical analysis and behavioral automaton experiments, which has the features of identifying states and neighborhoods of behavior, behavior recognition, using logistic regression and Bayes formulas, in particular, for machine learning. The verification model makes it possible to increase the completeness and accuracy of analysis to In(/S/
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*/L/), verification and forecasting, and the methods based on it reduce the computational complexity to In(/S/!) and increase the efficiency of predicting the reliable functioning of distributed data storage systems.