Satellite-Assisted UAV Data Collection for Information Freshness in IoRT Networks

Utilizing UAVs and satellites can offer an effective means to collect data for the Internet of remote things (IoRT) networks. However, due to the limited energy of UAVs and the high cost of satellite communication, ensuring the reduction of UAV energy consumption and communication costs while collecting fresh data poses a significant challenge. In this paper, we explore the issue of data gathering in IoRT networks with the assistance of UAVs and satellites. The UAV gathers data from sensor nodes (SNs) and decides whether to relay the collected data via satellite or send it directly to the data processing center. We handle this problem by formulating it as a Markov decision process to minimize the combined weighted sum of the average age of information, the energy consumption of the UAV, and communication costs through the implementation of a compound-action proximal policy optimization (CPPO) method. It can handle the compound actions of the UAV. This approach simultaneously optimizes the UAV's path, SN scheduling, and transmission decisions. Simulation results demonstrate that our algorithm can achieve better performance compared to baseline methods.