Model of hierarchical mobile radio network data flow management system

The article proposes a model of a hierarchical system of managing data flows of a mobile radio network, based on the interaction of intelligent agents and using neural inference. The essence of the development of this model is to describe the data flow management system in the form of a hierarchical distribution of the process of receiving and processing input data in the data flow management system. This model uses a multi-agent system to represent knowledge about the external environment of the system in the form of a mathematical model of an agent with different possible states. Next, the multi-agent system is presented in the form of a graph, using graph theory to describe the data flow management system and their interaction processes. Then the formation of a neural output with fuzzy sets occurs, as a result of which all received fuzzy input data will be reduced to a clear appearance. The next step involves the use of a neural network. At the last step, a simulation model is developed using a tool for its implementation. иThis will make it possible to simulate the control and switching system, digital data processing, taking into account the behavior caused by various external factors, taking into account the peculiarities of the use of the model in mobile radio networks. In general, the essence of creating an intelligent management system using a hierarchical decision-making support system is the possibility of interaction between elements of different types of networks using decision-making systems, by exchanging information when making management decisions. The developed model will make it possible to systematize the design process of the data flow management system in mobile radio networks, hierarchically distribute the process of receiving and processing input data, reduce the time of data processing and loading of the node and network resources used, using multi-agent systems, neural inference and modeling.