Computer Science ›› 2022, Vol. 49 ›› Issue (6): 25-31.doi: 10.11896/jsjkx.211100198

• Smart IoT Technologies and Applications Empowered by 6G • Previous Articles     Next Articles

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).

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

CLC Number: 

  • TN915.81
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