V2X多节点协同分布式卸载策略

曹敦; 张应宝; 邹电; 王进; 汤强; 冀保峰

doi:10.11959/j.issn.1000-436x.2022029

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V2X多节点协同分布式卸载策略

学术通信 | 更新时间：2024-06-05

- V2X多节点协同分布式卸载策略
- Multi-node cooperative distributed offloading strategy in V2X scenario
- 通信学报 2022年43卷第2期页码：185-195
- 作者机构：
  
  1. 长沙理工大学计算机与通信工程学院，湖南长沙 410114
  2. 南京邮电大学宽带无线通信与传感网技术教育部重点实验室，江苏南京 210003
  3. 河南科技大学信息工程学院，河南洛阳 471023
- 作者简介：
  
  [ "曹敦（1979-），女，湖南耒阳人，博士，长沙理工大学副教授、硕士生导师，主要研究方向为车联网和MIMO无线通信等" ]
  [ "张应宝（1997-），男，甘肃天水人，长沙理工大学硕士生，主要研究方向为移动边缘计算" ]
  [ "邹电（1992-），男，湖南岳阳人，长沙理工大学硕士生，主要研究方向为数字孪生" ]
  [ "王进（1979-），男，江苏扬州人，博士，长沙理工大学教授、博士生导师，主要研究方向为物联网、车联网和无线传感网等" ]
  [ "汤强（1982-），男，湖南岳阳人，博士，长沙理工大学讲师、硕士生导师，主要研究方向为智能电网、无线网络和移动计算等" ]
  [ "冀保峰（1985-），男，河南洛阳人，博士，河南科技大学副教授，主要研究方向为短距离协同传输毫米波MIMO、自适应信号处理等" ]
- 基金信息：
  
  国家自然科学基金资助项目(61902041);国家自然科学基金资助项目(61801170);湖南省自然科学基金资助项目(2021JJ30736);长沙市自然科学基金资助项目(kq2014112);南京邮电大学宽带无线通信与传感网技术教育部重点实验室开放研究基金资助项目(JZNY202102)
- DOI：10.11959/j.issn.1000-436x.2022029
  中图分类号： TN92
- 网络首发：2022-02，
  
  纸质出版：2022-02-25
- 稿件说明：
移动端阅览
曹敦, 张应宝, 邹电, 等. V2X多节点协同分布式卸载策略[J]. 通信学报, 2022,43(2):185-195.

Dun CAO, Yingbao ZHANG, Dian ZOU, et al. Multi-node cooperative distributed offloading strategy in V2X scenario[J]. Journal on Communications, 2022, 43(2): 185-195.
曹敦, 张应宝, 邹电, 等. V2X多节点协同分布式卸载策略[J]. 通信学报, 2022,43(2):185-195. DOI： 10.11959/j.issn.1000-436x.2022029.

Dun CAO, Yingbao ZHANG, Dian ZOU, et al. Multi-node cooperative distributed offloading strategy in V2X scenario[J]. Journal on Communications, 2022, 43(2): 185-195. DOI： 10.11959/j.issn.1000-436x.2022029.

摘要

为了应对车联网中计算资源密集、可分离型任务的卸载环境动态变化和不同协同节点通信、计算资源存在差异的问题，提出了一种在 V2X 下多协同节点串行卸载、并行计算的分布式卸载策略。该策略利用车辆可预测的行驶轨迹，对任务进行不等拆分，分布式计算于本地、MEC及协同车辆，建立系统时延最小化的优化问题。为求解该优化问题，设计了博弈论的卸载机制，以实现协同节点串行卸载的执行顺序；鉴于车联网的动态时变特性，利用序列二次规划算法，给出了最优的任务不等拆分。仿真结果表明，所提策略能够有效减少计算任务系统时延，且当多协同节点分布式卸载服务时，所提策略在不同的参数条件下仍然能够保持稳定的系统性能。

Abstract

In order to cope with the dynamic changes of the offloading environment for computing resource-intensive and separable tasks in Internet of vehicle and deal with the problem that different collaborative nodes had different communication and computing resources

a distributed offloading strategy that multiple collaborative nodes had serial offloading mode and parallel computing mode in vehicle to everything (V2X) scenario was proposed.Utilizing the predictable motion trajectories of vehicle

the tasks were split into unequal parts

finally each part was computed on itself

mobile edge server

and vehicles in parallel.Then an optimization problem of the system time delay minimization was established.To solve the optimization problem

an offloading scheme based on the game theory was designed to determine the serial offloading execution order of the cooperative nodes.Considering the dynamic characteristics of Internet of vehicles

a sequential quadratic programming (SQP) algorithm was adopted to optimally split tasks.Finally

the simulation results show that the proposed strategy can effectively reduce system delay

and when multiple cooperative nodes offload in parallel

the proposed strategy can still maintain the stable system performance under the different parameter conditions.

关键词

Keywords

references

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