Fault-Tolerant Scheduling of Heterogeneous UAVs for Data Collection of IoT Applications

UAV-enabled data collection is considered a promising paradigm of emergency data transmission for IoT applications when the communication infrastructure is damaged. UAV scheduling for data collection as critical technology has attracted widespread attention. Most studies default to the absolute reliability of UAVs for data collection, yet it is inevitable for UAVs to fail in flight. It is unacceptable if some critical data is lost due to UAV faults. Therefore, we research fault-tolerant scheduling for data collection enabled by heterogeneous UAVs. Firstly, a three-layer data collection motivation scenario is proposed, where the fault tolerance issue is involved for the first time. Then, we propose a utility-based fault tolerance model-UBFT to balance the reliability and efficiency of data collection. The UAV fault-tolerant scheduling is modeled as a multi-objective optimization problem to concurrently optimize the data throughput and load balancing of data collection. Combining the characteristics of optimization objectives, an alternating coordinate optimization method-ACTOR is presented to solve this problem efficiently. Numerous simulation experiments and real-machine experiments demonstrate that ACTOR-UBFT achieves excellent performance in fault tolerance, data throughput, adaptation, algorithm complexity, etc.