计算机科学 ›› 2022, Vol. 49 ›› Issue (6A): 601-605.doi: 10.11896/jsjkx.210200114

• 计算机网络 • 上一篇    下一篇

D2D辅助移动边缘计算下的卸载策略优化

方韬1, 杨旸1, 陈佳馨2   

  1. 1 陆军工程大学通信工程学院 南京 210007
    2 南京航空航天大学电子信息工程学院 南京 211106
  • 出版日期:2022-06-10 发布日期:2022-06-08
  • 通讯作者: 杨旸(sheep_1009@163.com)
  • 作者简介:(fangtaolgdx@163.com)
  • 基金资助:
    国家自然科学基金(61671474);江苏省杰出青年基金(BK20180028);江苏省优秀青年基金项目(BK20170089);江苏省研究生科研与实践创新计划(KYCX19_0188)

Optimization of Offloading Decisions in D2D-assisted MEC Networks

FANG Tao1, YANG Yang1, CHEN Jia-xin2   

  1. 1 College of Communications Engineering,Army Engineering University of PLA,Nanjing 210007,China
    2 College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China
  • Online:2022-06-10 Published:2022-06-08
  • About author:FANG Tao,born in 1993,postgraduate.His main research interests include game theory,D2D technology and machine learning.
    YANG Yang,born in 1983,associate professor.Her main research interests include UAV-assisted communications and dynamic spectrum sharing in wireless communications.
  • Supported by:
    National Natural Science Foundations of China(61671474),Jiangsu Provincial Natural Science Fund for Outstanding Young Scholars(BK20180028),Jiangsu Provincial Natural Science Fund for Excellent Young Scholars(BK20170089) and Postgraduate Research and Practice Innovation Program of Jiangsu Province(KYCX19_0188).

摘要: 移动边缘计算(Mobile Edge Computing,MEC)因具备资源下沉等特性能够为用户提供便捷的计算服务。为了进一步降低海量用户以及智能应用带来的卸载压力,考虑利用终端直传(Device-to-Device,D2D)通信技术实现用户闲置计算资源的合理利用。即除本地计算外,计算密集型用户还可以启用D2D通信方式,将复杂计算任务卸载至已配对的帮助用户。首先,将优化问题建模为最小化全网用户的累积时延。然后,为了分析多用户间的资源竞争问题和降低复杂度,引入博弈论,将优化问题建模为多用户合作卸载博弈,并证明所提博弈为精确势能博弈且拥有至少一个纯策略纳什均衡解。同时,提出基于较优响应的分布式卸载算法来实现问题的求解。最后,仿真结果表明,所提博弈模型和算法能够有效降低全网用户的总时延和平均用户时延,验证了工作的可行性及有效性。

关键词: D2D, 博弈论, 时延最小化, 卸载决策, 移动边缘计算

Abstract: Mobile edge computing(MEC) can provide convenient service for users due to the properties of resource subsidence.To further reduce the offloading pressure caused by massive users and smart applications,this paper utilizes device-to-device(D2D) technology to achieve reasonable utilization of idle local resources.That is,the compute-intensive users can offload their complex tasks to their idle neighbors in the proximity by D2D communications besides the local computing.First,the problem is formulated to minimize the aggregate delay of all users.Then,to analyze the resource competition among users and reduce the complexity,game theory is introduced and the multi-user cooperation offloading game is proposed.The proposed game is proved to be an exact potential game with at least one pure-strategy nash equilibrium(NE).Meanwhile,this paper proposes a better reply based distributed offloading algorithm to obtain the desired solution.Finally,simulation results show that the formulated game model and the proposed algorithm can decrease the network delay and average delay effectively,which validates the feasibility and effectiveness of our work.

Key words: Delay minimization, Device-to-Device, Game theory, Mobile edge computing, Offloading decision

中图分类号: 

  • TN929.5
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