DISTRIBUTED SIMULATION OF HETEROGENEOUS SYSTEMS OF THE INTERNET OF THINGS

Abstract

The article is devoted to the research and development of a distributed modelling system for heterogeneous Internet of Things (IoT) systems. In the current conditions of IoT technology development, there is a need to create effective methods for resource management, data synchronization, and ensuring the interaction of a large number of devices. Existing models and modelling systems have a number of limitations, in particular, high delays in data processing, limited scalability, and significant requirements for computing resources. The paper proposes a three-level distributed modelling architecture that allows for effective management of the interaction of IoT devices. The architecture consists of a distributed virtual network modelling layer, an interaction and control layer, and a shared communication service layer. Such a structure allows for increasing system performance, ensuring rapid synchronization of object states, and reducing the load on central computing nodes. An analysis of modern approaches to resource management and optimization of computing processes in IoT systems is conducted. Algorithms for object state synchronization, task distribution between nodes, and load balancing mechanisms are studied. A dynamic resource redistribution method is proposed, which allows adaptively changing the system configuration depending on the current load. Experimental modelling has demonstrated a reduction in data exchange delays, improved synchronization, and increased resource allocation efficiency. The proposed approach can be used in various areas, including smart cities, automated manufacturing, transportation systems, and the industrial Internet of Things. The research results open up prospects for further optimization of IoT network control algorithms, integration of artificial intelligence for load forecasting, and development of new methods for adaptive resource balancing.