基于多队列CQF的UANET业务调度机制研究

缪霏阳; 白丁月; 张策; 张暘; 李大鹏; 赵海涛

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基于多队列CQF的UANET业务调度机制研究

更新时间：2026-03-03

- 基于多队列CQF的UANET业务调度机制研究
- Research on Multi-Queue CQF-Based QoS Scheduling Mechanism for UANET
- 物联网学报 2026年
- 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：
  
  缪霏阳，feiyangmiao@163.com
- 基金信息：
  
  国家自然科学基金项目(U24B201873)
- DOI：
  中图分类号： TP391.2
- 收稿：2025-07-31，
  
  修回：2025-10-10，
  
  录用：2026-02-09，
- 稿件说明：
移动端阅览
缪霏阳, 白丁月, 张策, 等. 基于多队列CQF的UANET业务调度机制研究[J/OL]. 物联网学报, 2026.

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.
缪霏阳, 白丁月, 张策, 等. 基于多队列CQF的UANET业务调度机制研究[J/OL]. 物联网学报, 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

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