Fair Data Allocation and Trajectory Optimization for UAV-Assisted Mobile Edge Computing

被引：78

作者：

Diao, Xianbang ^{[1
]}

Zheng, Jianchao ^{[1
,2
]}

Cai, Yueming ^{[1
]}

Wu, Yuan ^{[3
,4
]}

Anpalagan, Alagan ^{[5
]}

机构：

[1] Army Engn Univ PLA, Coll Commun Engn, Nanjing 210007, Jiangsu, Peoples R China

[2] Acad Mil Sci PLA, Natl Innovat Inst Def Technol, Beijing 100010, Peoples R China

[3] Univ Macau, State Key Lab Internet Things Smart City, Macau, Peoples R China

[4] Univ Macau, Dept Comp & Informat Sci, Macau, Peoples R China

[5] Ryerson Univ, Dept Elect & Comp Engn, Toronto, ON M5B 2K3, Canada

来源：

IEEE COMMUNICATIONS LETTERS | 2019年 / 23卷 / 12期

基金：

中国国家自然科学基金;

关键词：

Task analysis; Energy consumption; Resource management; Servers; Trajectory optimization; Fairness; mobile edge computing; task data allocation; trajectory optimization; COMMUNICATION;

D O I：

10.1109/LCOMM.2019.2943461

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

This letter investigates fairness-aware task data allocation and trajectory optimization in unmanned aerial vehicles (UAV)-assisted mobile edge computing (MEC) systems, where a fixed-wing UAV is used as a flying computing server to receive task data of mobile terminals (MTs). Under the fairness consideration, we aim to minimize the maximum energy consumption among all MTs. Despite the non-convexity of the original formulated joint optimization problem, we transform the problem into two convex sub-problems by introducing auxiliary variables, and solve them jointly by proposing an iterative algorithm. Simulation results show that the proposed algorithm can effectively reduce the maximum energy consumption among all MTs.

引用

页码：2357 / 2361

页数：5

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