[2] SUN Haoran,GENG Suiyan,LIU Jiayan,et al. Joint device association and trajectory optimization for multi-UAV enabled power transmission and distribution scenarios[C]// 2023 5th International Conference on Electronic Engineering and Informatics(EEI).Wuhan,China:IEEE, 2023:546-550. doi:10.1109/EEI59236.2023.10212838.
[3] HUANG Guozheng, CHEN Gang, YI Jin, et al. Workload modelling method of edge computing terminals for distribution service under power Internet of Things[C]// 2021 6th Asia Conference on Power and Electrical Engineering(ACPEE). Chongqing,China:IEEE, 2021:430-435. doi:10.1109/ACPEE51499.2021.9436893.
[6] CHEN Xing, LIU Guizhong. Energy-efficient task offloading and resource allocation via deep reinforcement learning for augmented reality in mobile edge networks[J]. IEEE Internet of Things Journal, 2021, 8(13): 10843-10856. doi: 10.1109/JIOT.2021.3050804.
[8] LUO Jia,CHEN Qianbin,TANG Lun,et al. Adaptive resource allocation considering power consumption outage:a deep reinforcement learning approach[J]. IEEE Transactions on Vehicular Technology, 2023,72(6):8111-8116. doi:10.1109/TVT.2023.3237730.
[9] YANG Jing,ZHONG Yi,GE Xiaohu,et al. Power-consumption outage challenge in next-generation cellular networks[C]// 2019 IEEE Global Communications Conference(GLOBECOM). Waikoloa,HI,USA:IEEE, 2019:1-6. doi:10.1109/GLOBECOM38437.2019.9013860.
[10] YANG Jing, GE Xiaohu, THOMPSON J, et al. Power-consumption outage in beyond fifth generation mobile communication systems[J]. IEEE Transactions on Wireless Communications, 2021,20(2):897-910. doi:10.1109/TWC.2020.3029051.
[11] LU Junyu,LI Qiang,GUO Bing,et al. A multi-task oriented framework for mobile computation offloading[J]. IEEE Transactions on Cloud Computing, 2022,10(1):187-201. doi:10.1109/TCC.2019.2952346.