A Review of Game-Theoretic Approaches in Distributed IoT

Abstract

This paper comprehensively reviews game-theoretic approaches applied to distributed Internet of Things (IoT) systems. Game theory, focusing on strategic interactions among autonomous agents, offers valuable insights into optimizing various aspects of IoT networks, including resource allocation, security, load balancing, and network formation. We explore fundamental game-theoretic concepts and their traditional applications in distributed systems, highlighting how these models address the unique challenges of IoT environments. The review covers both cooperative and non-cooperative game theories and advanced models such as differential games and evolutionary game theory. Additionally, we discuss the integration of game theory with emerging technologies like blockchain, 5G, and edge computing, as well as the application of multi-objective optimization to balance conflicting goals within IoT networks. The paper also examines limitations such as scalability, computational complexity, and real-world implementation challenges. By synthesizing existing research and identifying future directions, this review aims to advance the understanding and application of game-theoretic approaches in enhancing distributed IoT systems' performance, security, and efficiency.