INTELLIGENT ENERGY CONSUMPTION MANAGEMENT IN EDGE COMPUTING NETWORKS BASED ON GAME THEORY

With the development of edge computing and the Internet of Things (IoT) technologies, the relevance of optimizing energy consumption in distributed networks is increasing. Traditional energy management methods are often inefficient due to the lack of adaptation to dynamic load conditions and limited coordination capabilities between nodes. This paper presents a cooperative dynamic energy management model in edge computing networks based on game theory principles. The introduction identifies the main problems of modern edge computing systems, including high energy consumption, uneven load distribution, and limited adaptation capabilities to changing operating conditions. A review of current research in the field of energy-efficient management in edge computing is provided. The theoretical foundations section describes the key concepts underlying the proposed model. The principles of cooperative and non-cooperative games, Nash equilibrium, and energy optimization algorithms used for balancing node loads in the network are considered. The methodology section formulates a mathematical model that describes the behavior of edge computing network nodes as a dynamic game with incomplete in