Reliable Aerial-Computing-Assisted Digital Twin for Cognitive IoT: A Hierarchical Game Approach

The Cognitive Internet of Things (CIoT) represents an advanced paradigm that equips IoT devices with cognitive abilities, enabling them to perceive, communicate, learn, reason, and adapt intelligently. This forms a key enabler for next-generation industrial systems. However, the limited local computing resources of CIoT devices make it challenging to perform complex computational tasks. To address this limitation, we propose a CIoT architecture supported by Digital Twin (DT), where the DT serves as a one-to-one virtual replica of the CIoT device, functioning as a “brain” for virtual simulation, data analysis, and intelligent decision-making. We deploy the DT in the drones, which act as aerial computing servers, providing a flexible, scalable, and cost-effective solution, particularly in areas with limited infrastructure. However, selecting reliable drones and designing appropriate incentive mechanisms remain challenging. To address these issues, we propose a hierarchical game-theoretic framework. First, we develop a reputation evaluation model based on the Theory of Planned Behavior (TPB) and the subjective logic model, followed by a coalition game approach to select reliable drones. Under conditions of information asymmetry, we then design a contract theory-based incentive mechanism to encourage drone participation in DT task execution. The Age of Information (AoI) metric is used to ensure the freshness of DT tasks. Numerical results demonstrate the effectiveness of the proposed hierarchical game-theoretic framework and reputation evaluation scheme.