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Automatic Control and Computer Sciences

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01-12-2023

Analysis and Forecasting of States of Industrial Networks with Adaptive Topology Based on Network Motifs

Author: E. Yu. Pavlenko

Published in: Automatic Control and Computer Sciences | Issue 8/2023

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Abstract—

This article proposes an approach to study states of complex industrial networks with adaptive topology based on network motifs: statistically significant subgraphs of a larger graph. The presented analysis concerns the applicability of network motifs to characterizing the system’s performance and for short-, medium-, and long-term forecasting of system states. A smart grid network structure is used as an example: it is represented as a directed graph, in which the most frequent motifs are identified; several scenarios of attacks on network nodes are modeled, and a forecast of the network state is compiled. The results of experimental studies demonstrate the accuracy and consistency of the application of this mathematical tool to the considered problems.

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Title: Analysis and Forecasting of States of Industrial Networks with Adaptive Topology Based on Network Motifs
Author: E. Yu. Pavlenko
Publication date: 01-12-2023
Publisher: Pleiades Publishing
Published in: Automatic Control and Computer Sciences / Issue 8/2023
Print ISSN: 0146-4116
Electronic ISSN: 1558-108X
DOI: https://doi.org/10.3103/S0146411623080229

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