Robust Task Scheduling for Delay-Aware IoT Applications in Civil Aircraft-Augmented SAGIN

• Published in: IEEE transactions on communications Vol. 70; no. 8; pp. 5368 - 5385
• Main Authors: Chen, Qian, Meng, Weixiao, Han, Shuai, Li, Cheng, Chen, Hsiao-Hwa
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Access control; Aircraft; Algorithms; Computation offloading; Cross-layer optimization; Delay; Delays; Energy consumption; Internet of Things; Optimization; Preempting; Queuing theory; Rician channels; robust optimization; Robustness; Satellites; Scheduling; space-air-ground integrated networks; Task analysis; Task scheduling
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2022.3186997

Although 5G networks have enabled mobile users to get a better experience, task scheduling remains challenging for massive Internet of Things (IoT) devices in remote areas. This paper investigates the task scheduling problem for delay-aware IoT applications in civil aircraft-augmented space-air-ground integrated networks (CAA-SAGIN), where the normalized sky access platforms (SAPs) can collect and forward the terrestrial tasks. Specifically, we first propose an access control scheme for a non-preemptive priority queuing system and a transmission control scheme with cross-layer optimization. Secondly, considering the uncertain distribution of the transmission numbers and generated data, we formulate a robust two-stage stochastic optimization problem of delay minimization. With the proposed robust task scheduling with risk aversion (RTS-RA) algorithm, the original problem can be decomposed into two subproblems, which can be further transformed into tractable semi-definite program (SDP) problems respectively. Simulation results show that the cross-layer optimization scheme can achieve a good tradeoff between delay and throughput. Also, the RTS-RA algorithm outperforms the exiting offloading schemes in terms of end-to-end delay, transmitted data, and energy consumption with lower computational complexity.