Informatization distributed redundancy storage method based on AI technology

Abstract

The invention discloses an informatization distributed redundancy storage method based on an AI technology, and relates to the technical field of artificial intelligence. The method comprises the steps of receiving a data set, preprocessing the data set, and converting and substituting the data set into a data value model to obtain a value evaluation coefficient; performing security level classification on each piece of effective data through the value score threshold value and the value evaluation coefficient of each piece of effective data in the effective data set; determining a storage node set corresponding to each security level set, and predicting the storage nodes through the target memory network to obtain a fault probability; performing effective node judgment on the storage nodes according to a preset fault probability threshold value and the fault probability to obtain effective nodes; optimizing the effective node set to obtain an optimal storage scheme; and storing the effective data corresponding to each security level according to the corresponding optimal storage scheme. The data are subjected to grade storage division, so that the waste of storage resources is reduced; and fault detection is performed on the storage nodes, so that consumption of computing resources is reduced.

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