QoS-Aware Energy-Efficient Multi-UAV Offloading Ratio and Trajectory Control Algorithm in Mobile-Edge Computing

doi:10.1109/JIOT.2024.3452111

科研成果详情

题名	QoS-Aware Energy-Efficient Multi-UAV Offloading Ratio and Trajectory Control Algorithm in Mobile-Edge Computing
作者	Yin，Jiajie 1; Tang，Zhiqing 2,3; Lou，Jiong 4; Guo，Jianxiong2,5 ; Cai，Hui 6; Wu，Xiaoming 7,8; Wang，Tian 2; Jia，Weijia 2,5
发表日期	2024
发表期刊	IEEE Internet of Things Journal
卷号	11 期号:24 页码:40588-40602
摘要	Multiple unmanned aerial vehicle (UAV)-assisted mobile-edge computing (MEC) leverages UAVs equipped with computational resources as mobile-edge servers, providing flexibility and low-latency connections, especially beneficial in smart cities and the Internet of Things (IoT). Maximizing Quality of Services (QoS) while minimizing energy consumption necessitates developing a suitable offloading ratio and trajectory control algorithm for UAVs. However, existing research on UAV control algorithms overlooks significant challenges like the heterogeneity of user equipments (UEs) and offloading failures. Furthermore, there is a dearth of experimental validation in large-scale UAV-assisted MEC scenarios. To bridge these gaps, we introduce a QoS-aware energy-efficient multi-UAV offloading ratio and trajectory control algorithm (QEMUOT). Specifically, 1) a composite UE mobility model is proposed to enhance system heterogeneous modeling, encompassing models for high-speed, low-speed, and fixed UEs; 2) QEMUOT is devised using multiagent reinforcement learning algorithms to determine offloading ratio and trajectory control decisions. To tackle sparse reward space and offloading failures, we employ expert demonstrations for pretraining and enhance reward mechanisms; and 3) experimental simulations illustrate that our algorithm outperforms baseline algorithms in user QoS with reduced energy consumption and demonstrates superior scalability in scenarios with numerous UAVs and UEs.
关键词	Heterogeneous mobility pattern mobile-edge computing (MEC) multiagent deep reinforcement learning unmanned aerial vehicle (UAV)
DOI	10.1109/JIOT.2024.3452111
URL	查看来源
语种	英语English
Scopus入藏号	2-s2.0-85202737068
引用统计
文献类型	期刊论文
条目标识符	https://repository.uic.edu.cn/handle/39GCC9TT/13752
专题	北师香港浸会大学
通讯作者	Tang，Zhiqing
作者单位	1.Faculty of Arts and Sciences,Institute of Artificial Intelligence and Future Networks,Beijing Normal University,Zhuhai,519087,China 2.Institute of Artificial Intelligence and Future Networks,Beijing Normal University,Zhuhai,519087,China 3.Qilu University of Technology,Shandong Academy of Sciences,Key Laboratory of Computing Power Network and Information Security,Ministry of Education,Jinan,250014,China 4.Shanghai Jiao Tong University,Department of Computer Science and Engineering,Shanghai,200240,China 5.BNU-HKBU United International College,Guangdong Key Laboratory of AI and Multi-Modal Data Processing,Zhuhai,519087,China 6.Nanjing University of Posts and Telecommunications,School of Computer Science,Nanjing,210023,China 7.Qilu University of Technology,Shandong Academy of Sciences,Key Laboratory of Computing Power Network and Information Security,Ministry of Education,Shandong Computer Science Center,Jinan,250014,China 8.Shandong Fundamental Research Center for Computer Science,Shandong Provincial Key Laboratory of Computer Networks,Jinan,250014,China
推荐引用方式 GB/T 7714	Yin，Jiajie,Tang，Zhiqing,Lou，Jionget al. QoS-Aware Energy-Efficient Multi-UAV Offloading Ratio and Trajectory Control Algorithm in Mobile-Edge Computing[J]. IEEE Internet of Things Journal, 2024, 11(24): 40588-40602.
APA	Yin，Jiajie., Tang，Zhiqing., Lou，Jiong., Guo，Jianxiong., Cai，Hui., .. & Jia，Weijia. (2024). QoS-Aware Energy-Efficient Multi-UAV Offloading Ratio and Trajectory Control Algorithm in Mobile-Edge Computing. IEEE Internet of Things Journal, 11(24), 40588-40602.
MLA	Yin，Jiajie,et al."QoS-Aware Energy-Efficient Multi-UAV Offloading Ratio and Trajectory Control Algorithm in Mobile-Edge Computing". IEEE Internet of Things Journal 11.24(2024): 40588-40602.