A data processing method that takes into account the mutual arrangement of information blocks in a computing cluster

Abstract

The development of information technologies entails the continuous improvement of tools that ensure the processing and transformation of confidential data. To solve such problems in real time, it is necessary to enhance the methods of data stream processing, as well as to evaluate their performance. The article discusses a mathematical model for the data transformation method based on the idea of cellular automaton with a floating window. To study the speed of the processing of confidential data, we developed a software module with a specific structure that includes a wider range of tuning parameters. These parameters include the activation string of the bit neighbourhood of the processed elements and the expansion rule for the boundary elements of the matrix which locates the neighbours of the processed element depending on the step of the algorithm. The article suggests a way to create a dependence diagram of the introduced changes, which indirectly reflects the strength of the encryption method and reveals whether the results comply with the confidence interval. Based on the results of the research, we developed a software unit implementing a rule that takes into account the state of the neighbouring data blocks for the processed element. The suggested approach to stream processing based on cellular automata and computing clusters allows us to optimise the speed of the data stream processing. This is possible due to the preliminary stage, when we assess the compliance of the current block to the custom template. At the same time, the results remained within the confidence interval and the bit distribution remained close to random. The article also describes the experiments we performed using the developed software unit that implements the data transformation method based on the idea of a cellular automaton with a floating window. The experimental study confirmed the completeness and correctness of the results obtained.