Distributed Matching Theory-Based Task Re-Allocating for Heterogeneous Multi-UAV Edge Computing

作     者：Yangang Wang Xianglin Wei Hai Wang Yongyang Hu Kuang Zhao Jianhua Fan Yangang Wang;Xianglin Wei;Hai Wang;Yongyang Hu;Kuang Zhao;Jianhua Fan

作者机构：College of Communications EngineeringArmy Engineering University of PLANanjing 210007China The Sixty-Third Research InstituteNational University of Defense TechnologyNanjing 210007China 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2024年第21卷第1期

页      面：260-278页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 082503[工学-航空宇航制造工程] 0835[工学-软件工程] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China under Grant 62171465 

主　　题：edge computing heterogeneity matching theory service function unmanned aerial vehicle 

摘      要：Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge ***,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not been fully considered ***,most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function(SF).In this backdrop,this paper formulates the task scheduling problem as a multi-objective task scheduling problem,which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks’completion time and energy *** three coupled goals in a realtime manner with the dynamic arrival of tasks hinders us from adopting existing methods,like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process,or heuristic-based ones that usually incur a long decision-making *** tackle this problem in a distributed manner,we establish a matching theory framework,in which three conflicting goals are treated as the preferences of tasks,SFs and ***,a Distributed Matching Theory-based Re-allocating(DiMaToRe)algorithm is put *** formally proved that a stable matching can be achieved by our *** simulation results show that Di Ma To Re algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.