ANALYSIS AND PREDICTION OF STATES OF INDUSTRIAL NETWORKS WITH ADAPTIVE TOPOLOGY BASED ON NETWORK MOTIFS
E. Yu. Pavlenko Peter the Great St. Petersburg Polytechnic University
Annotation: An approach to investigating the states of complex industrial networks with adaptive topology using network motifs – statistically significant subgraphs of a larger graph – is proposed. The analysis presented addresses the ability of network motifs to characterize system performance and the possibility of their application to short-, medium-, and long-term prediction of system states. Using the Smart Grid network structure as an example, a directed graph is modeled, in which the most common motifs are searched, several attack scenarios on network nodes are simulated and a network state prediction is built. The results of experimental studies confirmed the correctness and validity of the application of this mathematical apparatus for the set tasks
Keywords: dynamic graph, network motive, target function, network with adaptive topology, forecasting
Pages 94–108