Computing Power Networks for Unmanned Aerial Vehicles: A Hierarchical Resources Trading Market

Unmanned Aerial Vehicles (UAVs) are increasingly deployed across military and civilian domains due to their operational flexibility, low maintenance costs, and high mobility. With the growing complexity of UAV applications and tasks, robust support from computing power networks is essential. These networks, acting as resource integration paradigms, furnish UAVs with pooled resources to tackle extensive computational demands. In this paper, we develop a framework for trading computing power resources, modeling the transaction process through a three-stage Stackelberg game to facilitate sequential decision-making. We theoretically demonstrate the existence of a Nash equilibrium and introduce a Dynamic Game Reinforcement algorithm to identify optimal strategies. Our experimental results affirm the framework's efficacy and the superior performance of our algorithm. Additionally, we explore how variables like UAV quantity and network congestion influence the market dynamics of the computing power network.