Research on Multi-Queue CQF-Based QoS Scheduling Mechanism for UANET

MIAO Feiyang; BAI Dingyue; ZHANG Ce; ZHANG Yang; LI Dapeng; ZHAO Haitao

doi:null

您当前的位置：

首页 >

文章列表页 >

Research on Multi-Queue CQF-Based QoS Scheduling Mechanism for UANET

更新时间：2026-03-03

- Research on Multi-Queue CQF-Based QoS Scheduling Mechanism for UANET
- Chinese Journal on Internet of Things (2026)
- 作者机构：
  
  南京邮电大学通信与信息工程学院，江苏南京 210003
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(U24B201873)
- DOI：
  CLC： TP391.2
- Received：31 July 2025，
  
  Revised：2025-10-10，
  
  Accepted：09 February 2026，
- 稿件说明：
移动端阅览
MIAO Feiyang, BAI Dingyue, ZHANG Ce, et al. Research on Multi-Queue CQF-Based QoS Scheduling Mechanism for UANET[J/OL]. Chinese Journal on Internet of Things, 2026.
DOI：

MIAO Feiyang, BAI Dingyue, ZHANG Ce, et al. Research on Multi-Queue CQF-Based QoS Scheduling Mechanism for UANET[J/OL]. Chinese Journal on Internet of Things, 2026. DOI：

摘要

针对无人机自组网（Unmanned Aerial Vehicle Ad hoc Network

UANET）中，介质访问控制（Medium Access Control

MAC）层在混合业务流队列调度中服务质量（Quality of Service

QoS）保障机制存在的问题，提出了一种基于多队列循环队列转发（Cyclic Queuing and Forwarding

CQF）的业务调度机制（Multi-Queue CQF-Based QoS Scheduling Mechanism

MQSM）。该机制首先引入多队列CQF模型及相应调度策略，实现周期流和突发流的差异化传输需求，完成混合流的调度任务。然后，引入了一种融合GhostNet和SRResNet结构的时间资源调度算法（Time Resource Scheduling Algorithm Integrating GhostNet and SRResNet

GSR），以增强队列模型的调度性能并优化网络资源分配。最后，通过仿真验证所提出的GSR算法在混合数据流场景中具有良好的调度能力，能够合理地分配时间资源，实现低时延通信和模型的快速部署。

Abstract

To address the issues in MAC-layer Quality of Service (QoS) mechanisms for hybrid traffic queue scheduling in Unmanned Aerial Vehicle Ad Hoc Networks (UANETs)

a Multi-Queue CQF-Based QoS Scheduling Mechanism (MQSM) was proposed. Firstly

multi-queue CQF and corresponding scheduling strategies were introduced to meet the differentiated transmission requirements of periodic and bursty traffic

thus accomplishing the scheduling of hybrid flows. Then

a Time Resource Scheduling Algorithm Integrating GhostNet and SRResNet (GSR) was proposed to enhance the scheduling performance of the queue model and optimize network resource utilization. Finally

simulation results verify that the GSR algorithm demonstrates excellent scheduling capability in hybrid traffic scenarios

effectively allocating time resources to achieve low-latency communication and rapid model deployment.

关键词

Keywords

references

韩东升 , 郎宇航 , 黄丽妍 . 面向节点动态优先级的无人机信息收集优化算法 [J ] . 电子测量技术 , 2025 , 48 ( 9 ): 65 - 74 .

HAN D S , LANG Y H , HUANG L Y . Optimization algorithm for UAV information collection based on dynamic node priority [J ] . Electronic Measurement Technology , 2025 , 48 ( 9 ): 65 - 74 .

SATHISHKUMAR N , PALANISAMY S K , NATARAJAN R , et al . Experimental investigations of dual functional substrate integrated waveguide antenna with enhanced directivity for 5G mobile communications [J ] . Heliyon , 2024 , 10 ( 17 ): e36929 .

NWANERI I , AL-TURJMAN F . Application of artificial intelligence in mobile networks: a survey [M ] // Artificial Intelligence of Things (AIoT) . Cambridge : Morgan Kaufmann , 2025 : 15 - 22 .

BAI S , WANG X , GURSOY M C , et al . Deep Reinforcement Learning for Rechargeable UAV-Assisted Data Collection from Dense Mobile Sensor Nodes [J ] . IEEE Access , 2025 , 13 : 28398 - 28407 .

SUN C , FONTANESI G , CANBERK B , et al . Advancing uav communications: A comprehensive survey of cutting-edge machine learning techniques [J ] . IEEE Open Journal of Vehicular Technology , 2024 , ( 99 ): 1 - 31 .

马丁 . 基于无人机辅助无线通信性能优化研究 [D ] . 兰州交通大学 , 2021 .

MA D . Research on performance optimization of UAV-assisted wireless communication [D ] . Lanzhou : Lanzhou Jiaotong University , 2021 .

闵全 , 张格鹏 , 鲁晓飞 . 无线通信在复杂电磁环境下的抗干扰技术研究 [J ] . 数字技术与应用 , 2021 , 39 ( 04 ): 55 - 57 .

MIN Q , ZHANG G P , LU X F . Anti-jamming technology of wireless communication in complex electromagnetic environment [J ] . Digital Technology and Application , 2021 , 39 ( 04 ): 55 - 57 .

GUO J , GAO H , LIU Z , et al . ICRA: An intelligent clustering routing approach for UAV ad hoc networks [J ] . IEEE transactions on intelligent transportation systems , 2022 , 24 ( 2 ): 2447 - 2460 .

孙彦景 , 李林 , 王博文 , 等 . 灾后无人机自组网高动态多信道TDMA调度算法 [J ] . 西安电子科技大学学报 , 2024 , 51 ( 02 ): 56 - 67 .

SUN Y J , LI L , WANG B W , et al . High-dynamic multi-channel TD MA scheduling algorithm for UAV ad hoc networks after disaster [J ] . Journal of Xidian University , 2024 , 51 ( 02 ): 56 - 67 .

DASDEMIR E , BATTA R , KÖKSALAN M , et al . UAV routing for reconnaissance mission: A multi-objective orienteering problem with time-dependent prizes and multiple connections [J ] . Computers & Operations Research , 2022 , 145 : 105882 .

HAN S I . Survey on UAV deployment and trajectory in wireless communication networks: Applications and challenges [J ] . Information , 2022 , 13 ( 8 ): 389 .

MAXA J A , MAHMOUD M S B , LARRIEU N . Performance evaluation of a new secure routing protocol for UAV Ad hoc Network [C ] // 2019 IEEE/AIAA 38th Digital Avionics Systems Conference (DASC) . Piscataway : IEEE Press , 2019 : 1 - 10 .

张子东 , 宋志群 , 刘玉涛 , 等 . 基于TDMA的空中自组网MAC层资源调度算法研究 [J ] . 计算机测量与控制 , 2024 , 32 ( 01 ): 251 - 259 .

ZHANG Z D , SONG Z Q , LIU Y T , et al . Research on TDMA-based MAC layer resource scheduling algorithm for aerial ad hoc networks [J ] . Computer Measurement & Control , 2024 , 32 ( 01 ): 251 - 259 .

周佶昊 . 无线自组网资源调度方法研究 [D ] . 北京 : 北京邮电大学 , 2022 .

ZHOU J H . Research on resource scheduling methods for wireless ad hoc networks [D ] . Beijing : Beijing University of Posts and Telecommunications , 2022 .

SEAH W K G , LEE C H , LIN Y D , et al . Combined communication and computing resource scheduling in sliced 5G multi-access edge computing systems [J ] . IEEE Transactions on Vehicular Technology , 2021 , 71 ( 3 ): 3144 - 3154 .

LIANG B , OBaidat M S , LIU X , et al . Resource scheduling based on priority ladders for multiple performance requirements in wireless body area networks [J ] . IEEE Transactions on Vehicular Technology , 2021 , 70 ( 7 ): 7027 - 7036 .

ABBOU A N , TALEB T , SONG J S . A software-defined queuing framework for QoS provisioning in 5G and beyond mobile systems [J ] . IEEE Network , 2021 , 35 ( 2 ): 168 - 173 .

DOCQUIER T , SONG Y Q , CHEVRIER V . On the relevance of TSN for Substation Communication Networks [C ] // 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA) . Piscataway : IEEE Press, IEEE , 2022 : 1 - 8 .

WU Y , PAN W , CHEN Z , et al . Optimized Mapping and Hybrid Transmission Integrating TAS and CQF in TSN [C ] // 2024 8th International Conference on Communication and Information Systems (ICCIS) . Piscataway : IEEE Press , 2024 : 82 - 88 .

GHOSH A , KUNZ T , YOUSEFI S . Importance of realistic considerations of time synchronization for TAS in TSN networks [C ] // 2023 International Symposium on Networks, Computers and Communications (ISNCC) . Piscataway : IEEE Press , 2023 : 1 - 6 .

NIE H , LI S , LIU Y . TAMCQF: Hybrid traffic scheduling mechanism integrating tas and multi-cqf in tsn [C ] // 2023 IEEE Symposium on Computers and Communications (ISCC) . Piscataway : IEEE Press , 2023 : 329 - 334 .

ALEXANDRIS K , POP P , WANG T . Configuration and evaluation of multi-CQF shapers in IEEE 802.1 time-sensitive networking (TSN) [J ] . IEEE Access , 2022 , 10 : 109068 - 109081 .

YANG D , CHENG Z , ZHANG W , et al . Burst-aware time-triggered flow scheduling with enhanced multi-CQF in time-sensitive networks [J ] . IEEE/ACM Transactions on Networking , 2023 , 31 ( 6 ): 2809 - 2824 .

CHEN Y , XU L , LI L , et al . Cfs: A cqf-based fast scheduling scheme for time-sensitive networking [C ] // 2023 42nd Chinese Control Conference (CCC) . Piscataway : IEEE Press , 2023 : 6221 - 6226 .

丁奔程 . 基于时变流的时间敏感网络资源调度研究 [D ] . 成都：电子科技大学 , 2024 .

DING B C . Research on time-sensitive network resource scheduling based on time-varying flow [D ] . Chengdu : University of Electronic Science and Technology of China , 2024 .

李妍珏 . 时间敏感网络中的混合调度技术研究 [D ] . 北京：北京邮电大学 , 2023 .

LI Y J . Research on hybrid scheduling technology in time-sensitive networks [D ] . Beijing : Beijing University of Posts and Telecommunications , 2023 .

CHENG Z , YANG D , GUO R , et al . Joint time-frequency resource scheduling over CQF-based TSN-5G system [C ] // 2023 15th International Conference on Communication Software and Networks (ICCSN) . Piscataway : IEEE Press , 2023 : 60 - 65 .

于简豪 . 面向CQF模型的TSN资源调度算法的研究 [D ] . 沈阳：辽宁大学 , 2023 .

YU J H . Research on TSN resource scheduling algorithm for CQF model [D ] . Shenyang : Liaoning University , 2023 .

聂宏蕊 . 时间敏感网络流量调度机制研究 [D ] . 北京：北京邮电大学 , 2024 .

NIE H R . Research on traffic scheduling mechanism in time-sensitive networks [D ] . Beijing : Beijing University of Posts and Telecommunications , 2024 .

王文譞 . 面向车内网络确定性传输的数据调度及路由协同机制研究 [D ] . 成都：电子科技大学 , 2024 .

WANG W X . Research on data scheduling and routing coordination mechanism for deterministic transmission in in-vehicle networks [D ] . Chengdu : University of Electronic Science and Technology of China , 2024 .

SANDLER M , HOWARD A , ZHU M , et al . MobileNetV2: Inverted residuals and linear bottlenecks [C ] // Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . Piscataway : IEEE Press , 2018 : 4510 - 4520 .

HOWARD A , SANDLER M , CHU G , et al . Searching for MobileNetV3 [C ] // Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) . Seoul : IEEE Press , 2019 : 1314 - 1324 .

MA N , ZHANG X , ZHENG H-T , et al . ShuffleNet V2: Practical guidelines for efficient CNN architecture design [C ] // Proceedings of the European Conference on Computer Vision (ECCV) . Cham : Springer , 2018 : 128 - 138 .

TAN M , LE Q V . EfficientNet: Rethinking model scaling for convolutional neural networks [C ] // Proceedings of the 36th International Conference on Machine Learning (ICML) . Long Beach : Curran Associates, Inc. , 2019 : 10691 – 10700 .

HAN K , WANG Y , TIAN Q , et al . Ghostnet: More features from cheap operations [C ] // 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . Piscataway : IEEE Press , 2020 : 1577 - 1586 .

孔令鑫 , 陈紫强 , 晋良念 , 等 . 融合可变形卷积的轻量级路面病害检测算法 [J ] . 科学技术与工程 , 2025 , 25 ( 02 ): 683 - 694 .

KONG L X , CHEN Z Q , JIN L N , et al . Lightweight pavement disease detection algorithm fused with deformable convolution [J ] . Science Technology and Engineering , 2025 , 25 ( 02 ): 683 - 694 .

YUAN B , JACOB B , CHEN W , et al . Downscaling sea surface height and currents in coastal regions using convolutional neural network [J ] . Applied Ocean Research , 2024 , 151 : 104153 .

卢冰 , 李灿林 , 冯薛龙 , 等 . 基于改进SRResNet深度学习网络的低照度图像超分辨率重建方法 [J ] . 科学技术与工程 , 2022 , 22 ( 27 ): 12045 - 12052 .

LU B , LI C L , FENG X L , et al . Low-illumination image super-resolution reconstruction method based on improved SRResNet deep learning network [J ] . Science Technology and Engineering , 2022 , 22 ( 27 ): 12045 - 12052 .

AKHTAR M , TANVEER M , ARSHAD M . RoBoSS: A robust, bounded, sparse, and smooth loss function for supervised learning [J ] . IEEE Transactions on Pattern Analysis and Machine Intelligence , 2024 , 47 ( 1 ): 149 - 160 .

YAN J , QUAN W , JIANG X , et al . Injection time planning: Making CQF practical in time-sensitive networking [C ] // IEEE INFOCOM 2020-IEEE Conference on Computer Communications . Piscataway : IEEE Press , 2020 : 616 - 625 .

CHENG Z , YANG D , ZHANG W , et al . DeepCQF: Making CQF scheduling more intelligent and practicable [C ] // ICC 2022-IEEE International Conference on Communications . Piscataway : IEEE Press , 2022 : 1 - 6 .

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Lightweight attention-based SAR ship detector

A Wi-Fi sensing method for complex continuous human activities based on CNN-BiGRU

Research on cloud manufacturing service architecture and consensus algorithm based on blockchain technology

Research on a lightweight framework of industrial Internet-oriented manufacturing service collaboration level agreement

Vehicle detection based on SqueezeNet convolutional neural network

Related Author

LU Ping

ZHANG Hengjia

ZHU Ying

FENG Daquan

YU Nanjing

Anming DONG

You ZHOU

Kai ZHAO

Related Institution

State Key Laboratory of Mobile Network and Mobile Multimedia Technology

Zhongxing Telecom Equipment Corporation

China Academy of Information and Communications Technology

College of Electronics and Information Engineering, Shenzhen University

School of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences)

⁰