计算机科学 ›› 2022, Vol. 49 ›› Issue (6): 25-31.doi: 10.11896/jsjkx.211100198

• 6G 赋能智慧物联网技术与应用* 上一篇    下一篇

基于5G毫米波通信的高速公路车联网任务卸载算法研究

邱旭, 卞浩卜, 吴铭骁, 朱晓荣   

  1. 南京邮电大学江苏省无线通信重点实验室 南京 210003
  • 收稿日期:2021-11-18 修回日期:2022-02-22 出版日期:2022-06-15 发布日期:2022-06-08
  • 通讯作者: 朱晓荣(xrzhu@njupt.edu.cn)
  • 作者简介:(1460732039@qq.com)
  • 基金资助:
    国家自然科学基金(61871237,92067101);江苏省高校“青蓝工程”和江苏省重点研发计划(BE2021013-3)

Study on Task Offloading Algorithm for Internet of Vehicles on Highway Based on 5G MillimeterWave Communication

QIU Xu, BIAN Hao-bu, WU Ming-xiao, ZHU Xiao-rong   

  1. Jiangsu Key Laboratory of Wireless Communications,Nanjing University of Posts and Telecommunication,Nanjing 210003,China
  • Received:2021-11-18 Revised:2022-02-22 Online:2022-06-15 Published:2022-06-08
  • About author:QIU Xu,born in 1995,postgraduate.His main research interests include task offloading and resource allocation in Internet of vehicles.
    ZHU Xiao-rong,born in 1977,Ph.D,professor,Ph.D supervisor.Her main research interests include 5G communication system,heterogeneous network and Internet of Things.
  • Supported by:
    National Natural Science Foundation of China(61871237,92067101) and “Blue Project” of Universities in Jiangsu Province and Key R & D Program of Jiangsu Province(BE2021013-3).

摘要: 随着车联网的快速发展,不断涌现的新型车载任务对通信、计算能力提出了更高的要求。5G毫米波基站的大量部署为高速公路车辆用户提供了更加高速可靠的服务。同时,移动边缘计算技术将具有计算和存储能力的MEC(Mobile Edge Computing)服务器部署在用户终端周围,为车载任务提供计算服务的同时降低了传输时延。文中针对高速公路场景下车辆任务的卸载决策及通信资源分配问题,将计算及通信资源联合优化问题建模为0-1混合整数线性规划问题。首先,将原优化问题解耦为资源块分配子问题及卸载决策子问题;其次,使用注水算法及粒子群算法分别对子问题进行求解;最后,基于启发式算法对子问题进行迭代求解,以获得最优的资源块分配方案及卸载决策向量。仿真结果表明,该算法可在满足所有车载任务需求的同时最小化系统平均时延。

关键词: 粒子群算法, 任务卸载, 注水算法, 资源分配

Abstract: With the rapid development of the Internet of vehicles,the emerging new types of in-vehicle tasks put forward higher requirements for communication and computing capabilities.The development of satellite communication technology and the large-scale deployment of 5G millimeter-wave base stations provide safer and more reliable services for highway vehicle users.At the same time,mobile edge computing technology deploys mobile edge computing(MEC) servers with computing and storage capabi-lities around user terminals to provide computing services for on-board tasks while reducing transmission delays.Aiming at the problem of offloading decision-making and communication resource allocation of vehicle tasks in highway scenarios,the joint optimization problem of computing and communication resources is modeled as a 0-1 mixed integer linear programming problem.Firstly,the original optimization problem is decoupled into the resource block allocation sub-problem and the offloading decision sub-problem.Secondly,the sub-problems are solved by using the water injection algorithm and the particle swarm algorithm.Finally,the sub-problems are iteratively solved based on the heuristic algorithm to obtain the optimal resource block allocation scheme and offload decision vector.Simulation results show that the algorithm minimizes the average system delay while meeting the requirements of all on-board missions.

Key words: Particle swarm optimization, Resource allocation, Task offload, Water injection algorithm

中图分类号: 

  • TN915.81
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