Game Theory for Distributed Task Scheduling in Mist Computing

Mist computing addresses limitations in cloud and fog architectures by enabling computational resources closer to IoT devices, ensuring low latency and efficient resource utilization. Task scheduling in such environments poses challenges due to dynamic workloads, resource constraints, and network variability. This research introduces a game-theoretic framework for distributed task scheduling, leveraging non-cooperative game models to optimize resource allocation, reduce system latency, and improve energy efficiency. Through simulation-driven validation, the proposed mechanism demonstrates significant improvements in task completion time, resource utilization, and system scalability, paving the way for practical applications in IoT and real-time systems.