AoI-Sensitive Collaborative Data Generation and Collection for Multi-UAV-Assisted IoT Networks

Unmanned Aerial Vehicles (UAVs) are extensively used to collect sensing data from Internet of Things (IoT) networks. Facing with widely distributed Sensor Nodes (SNs), multiple UAVs collaborate to accomplish coverage access of SNs. Age of Information (Aol) is utilized to evaluate the timeliness of sensing data. However, SNs encounter a trade-off between remaining inactive to extend their lifespan and data generation to ensure task sensing requirements. Limited coverage capabilities lead to UAVs frequently traveling between SNs, consuming energy and reducing collection efficiency. Delays in information updates arise from the unsynchronized between UAV cruising times and the dynamic sensing frequencies of SNs. To tackle these challenges, we propose an multi-UAV collaboration framework that integrates coordinated data generation from SNs with UAV data collection. Additionally, we design an AoI and Energy Consumption Minimization (AECM) algorithm to jointly optimize sensing frequencies, UAV state switching, trajectory planning, and SN association. Simulation results demonstrate that our algorithm reduces energy consumption by 30 % while achieving a significantly lower AoI compared to traditional methods.