AGENT-BASED MODELING OF THE BEHAVIOR OF A DISTRIBUTED IOT SYSTEM FOR PRINTING PRODUCTION

Abstract

This paper presents an agent-based modeling approach to the behavior of distributed Internet of Things (IoT) systems designed for use in industrial printing environments. The study focuses on the development of a decentralized architecture, in which each functional component of the system operates as an autonomous agent capable of local decision-making, real-time sensor-actuator interaction, and peer-to-peer communication. A two-level control structure is proposed: the low-level control manages direct communication with sensors and actuators in real-time, while the high-level control performs contextual decision-making using ontology-driven logic and coordinates interactions between agents.

The model supports system self-adaptation and fault tolerance through dynamic reconfiguration mechanisms. In the event of node failures or changes in the network topology (e.g., adding a new functional unit), agents reorganize their connections and roles without centralized intervention. The paper includes behavioral pseudocode, architectural diagrams, and communication topology schemes that formalize the logic of interaction between components and enable virtual simulation of the system without the use of specialized software platforms.

The proposed agent-based approach demonstrates high flexibility, scalability, and robustness, making it well-suited for implementation in the printing industry, where operational conditions often require dynamic adaptation and intelligent control of technological processes. The research lays the groundwork for further development of digital twins, predictive maintenance strategies, and autonomous control systems in industrial IoT infrastructures.