A MODEL OF INTEGRATION AND STRUCTURAL OPTIMIZATION OF CYBER-PHYSICAL SYSTEM ELEMENTS

Abstract

The article presents the results of a study aimed at developing a model for the dynamic structural optimization of cyber-physical systems (CPS), which are built upon complex multi-level architectures integrating physical components with distributed computational processes. Using the example of modern monitoring systems in border security applications, it is demonstrated that the combination of multifunctional and structurally complex subsystems enables the implementation of adaptive optimization algorithms that more accurately account for both the internal system state and external operational conditions.

The proposed model is based on a multi-criteria approach that includes the ranking of competitive system configurations under conditions of incomplete or non-formalized information regarding optimality criteria. The study emphasizes the need to reconsider CPS optimization principles due to the high level of component interaction, dynamic load redistribution, and the integration of modern data analytics and machine learning algorithms. These factors result in emergent properties, nonlinear dependencies, and the need for structural reconfiguration of the system in response to changes in the operational environment.

The optimization model takes into account not only the activation of individual sensors or network nodes, but also evaluates resource consumption, system reliability, detection accuracy, and response time. The system’s performance is assessed under varying external conditions such as time of day and weather factors, necessitating dynamic adaptation to maintain specified operational parameters. The mathematical formalization includes the definition of structural and functional variables, objective functions, and probabilistic constraints on the effectiveness of sensors and communication subsystems.

The developed optimization model aims to minimize the average resource expenditures while satisfying constraints related to system performance and continuity of monitoring coverage. The proposed multi-criteria ranking approach enables the integration of diverse criteria — quantitative, qualitative, and linguistic — through normalization and projection into a unified analytical space. The paper provides examples of system configuration options and simulation results that demonstrate how optimal system states can be achieved under different operating conditions.

The proposed approach is particularly relevant to the design of CPS for border security applications, where complex technical systems must rapidly adapt to threats and environmental changes. Future research will be focused on solving inverse problems — determining the set of admissible system states based on constraints in the space of advantages and losses — which will enhance the adaptability and resilience of CPS architectures.