Bi-Objective Ant Colony Optimization for Trajectory Planning and Task Offloading in UAV-Assisted MEC Systems

doi:10.1109/TMC.2024.3408603

	Bi-Objective Ant Colony Optimization for Trajectory Planning and Task Offloading in UAV-Assisted MEC Systems
	Wang, Yiqian 1; Zhu, Jie 1,2; Huang, Haiping 3; Xiao, Fu 3
	2024-12-01
发表期刊	IEEE TRANSACTIONS ON MOBILE COMPUTING
ISSN	1536-1233
卷号	23 期号:12 页码:12360-12377
摘要	In the paper, the Unmanned Aerial Vehicle (UAV) path planning and task offloading problem in UAV-assisted mobile edge computing (MEC) systems is investigated. A bi-criterion ant colony optimization (bi-ACO) framework is proposed for the considered problem with the objectives of minimizing the total cost and the completion time, meanwhile satisfying the energy, deadline, location, and priority constraints. In the bi-ACO framework, multiple heterogeneous colonies are introduced with different preferences of objectives. Each colony maintains five pairs of pheromone matrices for constructing feasible solutions. Besides the colony settings, three key components of bi-ACO are delicately designed: feasible solution generation method (FSGM) to construct a feasible solution, solution division method (SDM) to improve obtained solutions of good quality, and pheromone update method (PUM) to updates pheromone matrices by pheromone evaporation operation and pheromone enhancement operation based on the preferences of colonies. Four Pareto-based metrics are introduced to evaluate the performance of the compared algorithms. Experimental results show that the proposal outperforms the compared baseline algorithms in effectiveness and robustness.
关键词	mobile edge computing Index Terms -ACO task offloading trajectory planning trajectory planning UAV UAV trajectory planning UAV
DOI	10.1109/TMC.2024.3408603
收录类别	SCI
语种	英语
资助项目	Jiangsu Province Universities Natural Science Research Major Project[23KJA520010] ; State Key Laboratory of Computer Architecture (ICT, CAS)[CARCHA202107] ; National Science Foundation for Postdoctoral Scientists of China[2018M640510] ; Natural Science Foundation of Jiangsu Province[BK20201375] ; National Natural Science Foundations of China[62072252]
WOS研究方向	Computer Science ; Telecommunications
WOS类目	Computer Science, Information Systems ; Telecommunications
WOS记录号	WOS:001359244600231
出版者	IEEE COMPUTER SOC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/41089
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Huang, Haiping
作者单位	1.Nanjing Univ Posts & Telecommun, Nanjing 210013, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, State Key Lab Chinese Comp Architecture, Beijing 100864, Peoples R China 3.Nanjing Univ Posts & Telecommun, Jiangsu High Technol Res Key Lab Wireless Sensor N, Nanjing 210013, Peoples R China
推荐引用方式 GB/T 7714	Wang, Yiqian,Zhu, Jie,Huang, Haiping,et al. Bi-Objective Ant Colony Optimization for Trajectory Planning and Task Offloading in UAV-Assisted MEC Systems[J]. IEEE TRANSACTIONS ON MOBILE COMPUTING,2024,23(12):12360-12377.
APA	Wang, Yiqian,Zhu, Jie,Huang, Haiping,&Xiao, Fu.(2024).Bi-Objective Ant Colony Optimization for Trajectory Planning and Task Offloading in UAV-Assisted MEC Systems.IEEE TRANSACTIONS ON MOBILE COMPUTING,23(12),12360-12377.
MLA	Wang, Yiqian,et al."Bi-Objective Ant Colony Optimization for Trajectory Planning and Task Offloading in UAV-Assisted MEC Systems".IEEE TRANSACTIONS ON MOBILE COMPUTING 23.12(2024):12360-12377.