面向差异化QoE基于匹配理论的任务卸载与资源分配方案

丁雷; 许晨; 刘斯宸; 谢星寰; 唐琳

doi:10.11959/j.issn.1000-0801.2025054

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面向差异化QoE基于匹配理论的任务卸载与资源分配方案

研究与开发 | 更新时间：2025-10-31

- 面向差异化QoE基于匹配理论的任务卸载与资源分配方案
- Differentiated QoE-oriented task offloading and resource allocation scheme based on matching theory
- 电信科学 2025年41卷第4期页码：107-116
- 作者机构：
  
  1.北京邮电大学人工智能学院，北京 100876
  2.北京微芯区块链与边缘计算研究院，北京 100876
- 作者简介：
  
  [ "丁雷（2000- ），男，北京邮电大学硕士生，主要研究方向为移动边缘计算、端边协同。" ]
  [ "许晨（1988- ），女，博士，北京邮电大学人工智能学院副教授、博士生导师，主要研究方向为边缘智能、协同通信与计算、智能网络优化。" ]
  [ "刘斯宸（2002- ），男，北京邮电大学硕士生，主要研究方向为移动边缘计算。" ]
  [ "谢星寰（2000- ），男，北京邮电大学硕士生，主要研究方向为车联网、无人机通信。" ]
  [ "唐琳（1987- ），男，博士，北京微芯区块链与边缘计算研究院副研究员、主任研究员，主要研究方向为数据分析与优化、区块链等技术创新及在政务、金融、食品、数据交易等不同领域的行业解决方案应用。" ]
- 基金信息：
  
  国家自然科学基金资助项目(62071179);国家重点研发计划项目(2022-YFB-2503202);未来区块链与隐私计算高精尖创新中心课题项目
- DOI：10.11959/j.issn.1000-0801.2025054
  中图分类号： TN929.5
- 收稿：2024-12-25，
  
  修回：2025-02-18，
  
  纸质出版：2025-04-20
- 稿件说明：
移动端阅览
丁雷,许晨,刘斯宸等.面向差异化QoE基于匹配理论的任务卸载与资源分配方案[J].电信科学,2025,41(04):107-116.

DING Lei,XU Chen,LIU Sichen,et al.Differentiated QoE-oriented task offloading and resource allocation scheme based on matching theory[J].Telecommunications Science,2025,41(04):107-116.
丁雷,许晨,刘斯宸等.面向差异化QoE基于匹配理论的任务卸载与资源分配方案[J].电信科学,2025,41(04):107-116. DOI： 10.11959/j.issn.1000-0801.2025054.

DING Lei,XU Chen,LIU Sichen,et al.Differentiated QoE-oriented task offloading and resource allocation scheme based on matching theory[J].Telecommunications Science,2025,41(04):107-116. DOI： 10.11959/j.issn.1000-0801.2025054.

摘要

随着6G通信网络和移动边缘计算（mobile edge computing，MEC）技术的迅速发展，配备边缘服务器的基站部署密度持续提高，计算任务呈现出日益多样化的趋势。为应对差异化用户体验质量（quality of experience，QoE）以及资源分配不均衡对系统性能的影响，提出了一种高效的匹配卸载方案，综合考虑了卸载决策以及计算资源分配，构建了一个以最大化系统收益为目标的混合整数非线性规划问题。通过分解原问题，基于双边匹配理论设计了一种迭代优化算法加以求解。仿真实验基于澳大利亚墨尔本中央商务区（central business district，CBD）的公共数据集进行验证，结果表明，与现有方案相比，所提方案在提升系统收益方面表现出显著的优势。

Abstract

With the rapid development of 6G communication networks and mobile edge computing(MEC) technology

the deployment density of base stations equipped with edge servers has been continuously increasing

and computational tasks show a growing trend toward diversification. To address the impact of differentiated quality of experience (QoE) for users and unbalanced resource allocation on system performance

an efficient matching offloading scheme was proposed. The scheme comprehensively considered both offloading decisions and computational resource allocation

and a mixed-integer nonlinear programming problem was formulated with the objective of maximizing system utility. By decomposing the original problem

an iterative optimization algorithm was designed based on bilateral matching theory for solution. Simulation experiments were conducted using public datasets from the central business district (CBD) of Melbourne

Australia. The results demonstrate that

compared with existing schemes

the proposed scheme shows significant advantages in improving system utility.

关键词

Keywords

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