Information and evaluation models of complex hierarchical network systems

TL;DR

This paper presents models for managing and evaluating complex hierarchical network systems, enabling more efficient decision-making through continuous monitoring, novelty detection, and analysis methods.

Contribution

It introduces new information and evaluation models based on regular studies and monitoring, incorporating evaluation theory for novelty detection in complex systems.

Findings

Models facilitate real-time monitoring and analysis

Evaluation methods improve decision-making speed

Novelty detection enhances system adaptability

Abstract

The problem of selection, storage, search and analysis of information about the state, functioning and interaction of elements of complex hierarchical network systems is considered. The principles of construction of information models of such systems and models of evaluation of their operation efficiency are proposed. These models are formed on the basis of results of regular planned studies of the system and continuous monitoring of the activities of its components at all levels of the hierarchy. The problem of novelty detection in the information model of system is investigated and it is shown how the application of evaluation theory methods allows to solve it. The proposed methods of complex analysis of the behavior of real complex systems and optimization of data processing makes it possible to significantly simplify and speed up the decision-making process for further action for such systems.