A Task Offloading Method for Vehicular Edge Computing Based on Reputation Assessment  

作　　者：Jun Li Yawei Dong Liang Ni Guopeng Feng Fangfang Shan 

机构地区：[1]School of Computer Science,Zhongyuan University of Technology,Zhengzhou,450007,China [2]Henan Key Laboratory of Cyberspace Situation Awareness,Zhengzhou,450007,China

出　　处：《Computers, Materials & Continua》2025年第5期3537-3552,共16页计算机、材料和连续体(英文)

基　　金：supported by the Open Foundation of Henan Key Laboratory of Cyberspace Situation Awareness(No.HNTS2022020);the Science and Technology Research Program of Henan Province of China(232102210134,182102210130);Key Research Projects of Henan Provincial Universities(25B520005).

摘　　要：With the development of vehicle networks and the construction of roadside units,Vehicular Ad Hoc Networks(VANETs)are increasingly promoting cooperative computing patterns among vehicles.Vehicular edge computing(VEC)offers an effective solution to mitigate resource constraints by enabling task offloading to edge cloud infrastructure,thereby reducing the computational burden on connected vehicles.However,this sharing-based and distributed computing paradigm necessitates ensuring the credibility and reliability of various computation nodes.Existing vehicular edge computing platforms have not adequately considered themisbehavior of vehicles.We propose a practical task offloading algorithm based on reputation assessment to address the task offloading problem in vehicular edge computing under an unreliable environment.This approach integrates deep reinforcement learning and reputation management to address task offloading challenges.Simulation experiments conducted using Veins demonstrate the feasibility and effectiveness of the proposed method.

关 键 词：Vehicular edge computing task offloading reputation assessment 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]