Journal of Xidian University ›› 2025, Vol. 52 ›› Issue (3): 176-187.doi: 10.19665/j.issn1001-2400.20250111

• The 27th Annual Meeting of The China Association for Science and Technology ——6G Technological Innovation and Future Industrial Development • Previous Articles     Next Articles

Vehicle-assisted adaptive task offloading strategy for the internet of vehicles

ZHANG Chao1(), ZHAO Hui1,2,3(), DONG Yuhang1(), TANG Hanqin2(), WANG Jing1(), WAN Bo1,2,3(), WANG Quan1,3()   

  1. 1. School of Computer Science and Technology,Xidian University,Xi’an 710126,China
    2. Hangzhou Institute of Technology,Xidian University,Hangzhou 311231,China
    3. Key Laboratory of Smart Human-Computer Interaction and Wearable Technology of Shaanxi Province,Xi’an 710126,China
  • Received:2024-12-16 Online:2025-06-20 Published:2025-01-21
  • Contact: WANG Jing E-mail:22031212431@stu.xidian.edu.cn;hzhao@mail.xidian.edu.cn;24031212270@stu.xidian.edu.cn;22031212300@stu.xidian.edu.cn;wangjing@mail.xidian.edu.cn;wanbo@xidian.edu.cn;qwang@xidian.edu.cn

Abstract:

With the rapid development of vehicular networking,edge servers with a limited computing power will delay the task completion time when facing the processing of a large amount of data,affecting the user experience.However,some vehicles traveling on the road may have idle resources under the premise of meeting their own needs,resulting in a waste of resources.In addition,retransmission of tasks due to instability of communication connections in dynamic telematics environments is also a key issue to be addressed.Aiming at the above problems,this paper proposes a vehicle-assisted adaptive task offloading strategy for the Internet of vehicles to reduce the task completion time.We categorize task offloading in the vehicular networking environment into the following two cases based on the relative position of the vehicle and the edge server,the communication coverage,and considering the vehicle’s driving state information.When the vehicle is not or is about to drive out of the edge server coverage,the task cannot be offloaded directly to the edge server,and then an optimal service vehicle selection algorithm is proposed to offload the task to the optimal service vehicle.When the vehicle is within the coverage range of the edge server,a task scheduling algorithm based on hybrid differential teaching optimization is proposed to offload the task to the optimal edge server.Finally,simulation experiments are designed to verify the effectiveness of the proposed task offloading strategy in comparison with existing methods.

Key words: internet of vehicles, task offloading, service vehicle, hybrid differential teaching optimization

CLC Number: 

  • TP393.09