Trajectory design and bandwidth allocation strategy in UAV-assisted MEC network

Xue JIANG; Liang ZHAO

doi:10.11959/j.issn.2096-3750.2023.00329

您当前的位置：

首页 >

文章列表页 >

Trajectory design and bandwidth allocation strategy in UAV-assisted MEC network

Theory and Technology | 更新时间：2024-08-16

- Trajectory design and bandwidth allocation strategy in UAV-assisted MEC network
- Chinese Journal on Internet of Things Vol. 7, Issue 4, Pages: 123-131(2023)
- 作者机构：
  
  1. 南京邮电大学，江苏南京 210003
  2. 杭州昊舜视讯科技有限公司，浙江杭州 310023
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-3750.2023.00329
  CLC： TN925
- Online First：2023-12，
  
  Published：20 December 2023
- 稿件说明：
移动端阅览
Xue JIANG, Liang ZHAO. Trajectory design and bandwidth allocation strategy in UAV-assisted MEC network[J]. Chinese Journal on Internet of Things, 2023, 7(4): 123-131.
DOI：

Xue JIANG, Liang ZHAO. Trajectory design and bandwidth allocation strategy in UAV-assisted MEC network[J]. Chinese Journal on Internet of Things, 2023, 7(4): 123-131. DOI： 10.11959/j.issn.2096-3750.2023.00329.

摘要

研究了在无人机（UAV

unmanned aerial vehicle）辅助移动边缘计算（MEC

mobile edge computing）网络中，单个UAV可以作为移动基站接收网络中多个用户设备卸载的数据场景。由于需要满足UAV的机动性、系统的计算时延和通信时延等要求，以最小化网络能耗为目标，提出了联合优化 UAV 三维飞行轨迹和用户设备带宽分配的方法。对应的非凸不易求解的优化问题转换为两个子优化问题，即在给定带宽的条件下 UAV 三维飞行轨迹优化的问题以及给定 UAV 三维飞行轨迹的条件下用户设备带宽分配策略的优化问题。仿真结果表明，所提算法的能耗明显低于另外两种典型算法。更进一步，本文为解决UAV辅助MEC网络中资源和能耗受限的问题提供了有力的理论依据。

Abstract

The unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) network

where the UAV can be used as a mobile base station to collect data from the multiple user devices was studied.Since it should satisfy the UAV velocity constraint

the system computation latency constraint

and the system communication latency constraint

a joint scheme of bandwidth allocation and UAV 3D trajectory was proposed to minimize the total energy consumption of the network.The corresponding non-convex optimization problem that is difficult to solve was converted into two sub-optimization problems

which are the UAV 3D trajectory optimization subproblem by fixing bandwidth allocation

and the user equipment bandwidth allocation subproblem by fixing UAV 3D trajectory.Experiments demonstrate that the energy consumption of the proposed algorithm is less than that of the other two typical algorithms.Furthermore

the theoretical basis for solving the limited resource and energy problem in UAV-assisted MEC network was provided.

关键词

Keywords

references

MAO Y Y , YOU C S , ZHANG J , et al . A survey on mobile edge computing:the communication perspective [J ] . IEEE Communications Surveys ＆ Tutorials , 2017 , 19 ( 4 ): 2322 - 2358 .

张开元 , 桂小林 , 任德旺 , 等 . 移动边缘网络中计算迁移与内容缓存研究综述 [J ] . 软件学报 , 2019 , 30 ( 8 ): 2491 - 2516 .

ZHANG K Y , GUI X L , REN D W , et al . Survey on computation offloading and content caching in mobile edge networks [J ] . Journal of Software , 2019 , 30 ( 8 ): 2491 - 2516 .

SHI W S , CAO J , ZHANG Q , et al . Edge computing:vision and challenges [J ] . IEEE Internet of Things Journal , 2016 , 3 ( 5 ): 637 - 646 .

LI P M , XU J . Fundamental rate limits of UAV-enabled multiple access channel with trajectory optimization [J ] . IEEE Transactions on Wireless Communications , 2020 , 19 ( 1 ): 458 - 474 .

XIE L F , XU J , ZHANG R . Throughput maximization for UAV-enabled wireless powered communication networks [J ] . IEEE Internet of Things Journal , 2019 , 6 ( 2 ): 1690 - 1703 .

GUPTA N , AGARWAL S , MISHRA D . Trajectory design for throughput maximization in UAV-assisted communication system [J ] . IEEE Transactions on Green Communications and Networking , 2021 , 5 ( 3 ): 1319 - 1332 .

LIU X , LAI B J , LIN B , et al . Joint communication and trajectory optimization for multi-UAV enabled mobile Internet of vehicles [J ] . IEEE Transactions on Intelligent Transportation Systems , 2022 , 23 ( 9 ): 15354 - 15366 .

冯建新 , 栾帅帅 , 刘俊梅 , 等 . 一种高吞吐量的UAV 轨迹规划方法 [J ] . 计算机工程 , 2021 , 47 ( 1 ): 172 - 181 .

FENG J X , LUAN S S , LIU J M , et al . An unmanned aerial vehicle trajectory planning method with high throughput [J ] . Computer Engineering , 2021 , 47 ( 1 ): 172 - 181 .

罗佳 , 陈前斌 , 唐伦 , 等 . 考虑能耗中断的UAV通信中基于深度强化学习的资源管理 [J ] . 电子与信息学报 , 2022 ( 45 ): 1 - 8 .

LUO J , CHEN Q B , TANG L , et al . Deep reinforcement learning based resource management for UAV communication considering power-consumption outage [J ] . Journal of Electronics ＆ Information Technology , 2022 ( 45 ): 1 - 8 .

LEE J H , PARK K H , KO Y C , et al . A UAV-mounted free space optical communication:trajectory optimization for flight time [J ] . IEEE Transactions on Wireless Communications , 2020 , 19 ( 3 ): 1610 - 1621 .

XU S , ZHANG X Y , LI C G , et al . Deep reinforcement learning approach for joint trajectory design in multi-UAV IoT networks [J ] . IEEE Transactions on Vehicular Technology , 2022 , 71 ( 3 ): 3389 - 3394 .

SAMIR M , SHARAFEDDINE S , ASSI C , et al . Trajectory planning and resource allocation of multiple UAVs for data delivery in vehicular networks [J ] . IEEE Networking Letters , 2019 , 1 ( 3 ): 107 - 110 .

周理辉 , 肖霖 , 吴法辉 , 等 . UAV 全双工双向中继的资源及轨迹优化设计 [J ] . 北京邮电大学学报 , 2023 , 46 ( 1 ): 77 - 83 .

ZHOU L H , XIAO L , WU F H , et al . Resource and trajectory optimal design for unmanned aerial vehicles full duplex two-way relay [J ] . Journal of Beijing University of Posts and Telecommunications , 2023 , 46 ( 1 ): 77 - 83 .

廖乃稳 , 何攀峰 , 张余 , 等 . UAV 中继通信的轨迹与资源分配优化方法 [J ] . 移动通信 , 2023 , 47 ( 2 ): 92 - 98 .

LIAO N W , HE P F , ZHANG Y , et al . Trajectory and resource allocation optimization method for UAV-relaying communication [J ] . Mobile Communications , 2023 , 47 ( 2 ): 92 - 98 .

HU Q Y , CAI Y L , YU G D , et al . Joint offloading and trajectory design for UAV-enabled mobile edge computing systems [J ] . IEEE Internet of Things Journal , 2019 , 6 ( 2 ): 1879 - 1892 .

郑鸿强 , 张建山 , 陈星 . 空-天-地一体化移动边缘计算系统的部署优化和计算卸载 [J ] . 计算机科学 , 2023 , 50 ( 2 ): 69 - 79 .

ZHENG H Q , ZHANG J S , CHEN X . Deployment optimization and computing offloading of space-air-ground integrated mobile edge computing system [J ] . Computer Science , 2023 , 50 ( 2 ): 69 - 79 .

李安 , 戴龙斌 , 余礼苏 , 等 . 加权能耗最小化的UAV辅助移动边缘计算资源分配策略 [J ] . 电子与信息学报 , 2022 , 44 ( 11 ): 3858 - 3865 .

LI A , DAI L B , YU L S , et al . Resource allocation for unmanned aerial vehicle-assisted mobile edge computing to minimize weighted energy consumption [J ] . Journal of Electronics ＆ Information Technology , 2022 , 44 ( 11 ): 3858 - 3865 .

崔高峰 , 徐媛媛 , 张尚宏 , 等 . 基于最小能耗的多UAV无线网络安全数据卸载策略 [J ] . 通信学报 , 2021 , 42 ( 5 ): 51 - 62 .

CUI G F , XU Y Y , ZHANG S H , et al . Secure data offloading strategy for multi-UAV wireless networks based on minimum energy consumption [J ] . Journal on Communications , 2021 , 42 ( 5 ): 51 - 62 .

DU Y , WANG K Z , YANG K , et al . Energy-efficient resource allocation in UAV based MEC system for IoT devices [C ] // Proceedings of 2018 IEEE Global Communications Conference (GLOBECOM) . Piscataway:IEEE Press , 2019 : 1 - 6 .

TUN Y K , PARK Y M , TRAN N H , et al . Energy-efficient resource management in UAV-assisted mobile edge computing [J ] . IEEE Communications Letters , 2021 , 25 ( 1 ): 249 - 253 .

ZHAO C X , LIU J Y , SHENG M , et al . Multi-UAV trajectory planning for energy-efficient content coverage:a decentralized learning-based approach [J ] . IEEE Journal on Selected Areas in Communications , 2021 , 39 ( 10 ): 3193 - 3207 .

陈阳 , 皮德常 , 代成龙 , 等 . 多UAV协同陆地设施辅助移动边缘计算的系统能耗最小化方法 [J ] . 电子学报 , 2023 , 51 ( 2 ): 1 - 9 .

CHEN Y , PI D C , DAI C L , et al . Energy minimization for a multi-UAVs cooperative ground access points assisted mobile edge computing [J ] . ACTA Electronica Sinica , 2023 , 51 ( 2 ): 1 - 9 .

夏景明 , 刘玉风 , 谈玲 . 基于蜂窝网络的多 UAV 能耗最优化算法研究 [J ] . 通信学报 , 2023 , 44 ( 2 ): 1 - 13 .

XIA J M , LIU Y F , TAN L . Research on energy consumption optimization algorithm of multi-UAV based on cellular network [J ] . Journal on Communications , 2023 , 44 ( 2 ): 1 - 13 .

余雪勇 , 朱烨 , 邱礼翔 , 等 . 基于UAV辅助边缘计算系统的节能卸载策略 [J ] . 系统工程与电子技术 , 2022 , 44 ( 3 ): 1022 - 1029 .

YU X Y , ZHU Y , QIU L X , et al . Energy efficient offloading strategy for UAV aided edge computing systems [J ] . Systems Engineering and Electronics , 2022 , 44 ( 3 ): 1022 - 1029 .

WANG L , WANG K Z , PANC H , et al . Multi-agent deep reinforcement learning-based trajectory planning for multi-UAV assisted mobile edge computing [J ] . IEEE Transactions on Cognitive Communications and Networking , 2021 , 7 ( 1 ): 73 - 84 .

吴启晖 , 吴伟 . UAV 辅助边缘计算的能量效率最大化算法设计 [J ] . 通信学报 , 2020 , 41 ( 10 ): 15 - 24 .

WU Q H , WU W . Algorithm design on energy efficiency maximization for UAV-assisted edge computing [J ] . Journal on Communications , 2020 , 41 ( 10 ): 15 - 24 .

ZHANG J , ZHOU L , ZHOU F H , et al . Computation-efficient offloading and trajectory scheduling for multi-UAV assisted mobile edge computing [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 2 ): 2114 - 2125 .

姚维 , 黄俊 . 移动边缘计算中的UAV群协同任务卸载策略研究 [J ] . 重庆邮电大学学报(自然科学版) , 2022 , 34 ( 3 ): 507 - 514 .

YAO W , HUANG J . Research on UAVs collaborative task offloading strategy based on mobile edge computing [J ] . Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition) , 2022 , 34 ( 3 ): 507 - 514 .

DIAO X B , ZHENG J C , CAI Y M , et al . Fair data allocation and trajectory optimization for UAV-assisted mobile edge computing [J ] . IEEE Communications Letters , 2019 , 23 ( 12 ): 2357 - 2361 .

Views

317

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Joint trajectory optimization and computation offloading strategy for space-air-ground integrated networks

Edge-assisted UAV onboard video compression and transmission for efficient inference of patrolling tasks

A sensing and control closed-loop scheduling strategy for UAV swarms

NOMA-based secure computation offloading in marine Internet of things

Partial computation offloading method based on joint resource allocation for mobile edge computing

Related Author

ZHANG Yuexia

ZHU Haoyang

LIU Mingliu

KONG Yuxin

LIANG Yuxin

YANG Peng

LIANG Qingquan

ZHANG Tingting

Related Institution

School of Information and Communication Engineering, Beijing Information Science & Technology University

School of Electronic Information and Communications, Huazhong University of Science and Technology

Electric Power Research Institute, State Grid Hubei Electric Power Co., Ltd.

Guangdong Provincial Key Laboratory of Space-Aerial Networking and Intelligent Sensing, Harbin Institute of Technology

School of Information Science and Technology, Harbin Institute of Technology

⁰