Computer Science ›› 2025, Vol. 52 ›› Issue (8): 354-362.doi: 10.11896/jsjkx.240700088

• Computer Network • Previous Articles     Next Articles

Effective Task Offloading Strategy Based on Heterogeneous Nodes

FAN Xinggang1, JIANG Xinyang1, GU Wenting1, XU Juntao1, YANG Youdong2, LI Qiang1   

  1. 1 College of Computer Science and Technology,Zhejiang University of Technology,Hangzhou 310023,China
    2 Zhijiang College of Zhejiang University of Technology,Shaoxing,Zhejiang 312030,China
  • Received:2024-07-15 Revised:2024-10-16 Online:2025-08-15 Published:2025-08-08
  • About author:FAN Xinggang,born in 1974,Ph.D,professor,is a member of CCF(No.74204M).His main research interests include sensor networks,network communication and Internet of Things.
    YANG Youdong,born in 1970,Ph.D,professor.His main research interests include computer-aided design and graphics and so on.
  • Supported by:
    “Pioneer” and “Leading Goose” R&D Program of Zhejiang(2023C01029,2025C01054).

Abstract: In vehicular edge computing(VEC),how to use the limited network resources to implement efficient task unloading is a research hotspot in recent years.This paper focuses on task offloading in the heterogeneous node mode and designs an efficient task offloading strategy in heterogeneous node mode(TOS-HN).When a vehicle generates a task,mobile node offloading is prio-ritized to offload the task to a nearby idle vehicle.If the mobile offloading cannot meet the task requirements,a fixed node offloa-ding strategy is adopted.In the mobile node offloading mode,the cost matrix is first constructed based on the task processing delay and energy consumption,and then the Hungarian algorithm is used to determine the optimal matching between the task vehicle and the processing vehicle.Simulation experiment proves that the TOS-HN algorithm has significant advantages over other algorithms,with better performance in terms of delay,energy consumption,task success rate and base station load.

Key words: Vehicular edge computing, Task offloading, Heterogeneous node mode, Mobile, Cost matrix

CLC Number: 

  • TP393
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