Computer Science ›› 2022, Vol. 49 ›› Issue (9): 242-248.doi: 10.11896/jsjkx.210700166

• Computer Network • Previous Articles     Next Articles

Dynamic Pricing-based Vehicle Collaborative Computation Offloading Scheme in VEC

SUN Hui-ting, FAN Yan-fang, MA Meng-xiao, CHEN Ruo-yu, CAI Ying   

  1. Computer School,Beijing Information Science & Technology University,Beijing 100101,China
  • Received:2021-07-15 Revised:2021-10-20 Online:2022-09-15 Published:2022-09-09
  • About author:SUN Hui-ting,born in 1996,postgra-duate.Her main research interests include Internet of vehicles,edge computing and computation offloading.
    FAN Yan-fang,born in 1979,Ph.D,is a member of China Computer Federation.Her main research interests include information security,vehicular networking and edge computing.
  • Supported by:
    National Natural Science Foundation of China(61672106),Natural Science Foundation of Beijing(L192023),Foundation of Beijing Information Science & Technology University(2025028),Promoting the Internal Development of Universities-Innovative Research Platform Project for Edge Computing(2020KYNH105),Open Project of Beijing Key Laboratory of Internet Culture and Digital Dissemination Research and Qinxin Talent Training Plan of Beijing Information Science & Technology University(QXTCP C202111).

Abstract: Vehicular edge computing(VEC) is an important application of mobile edge computing(MEC) in Internet of vehicles.In VEC,to meet the computing requirement of task vehicles(TaV),TaV can pay to offload tasks to the VEC server or service vehicles(SeV)with abundant idle computing resources.For the VEC provider,one of its goals is to maximize revenue.Since the computing requirements and the computing resources of the system change dynamically,it is an important issue to design a reasonable pricing strategy in vehicle collaboration scenarios.To solve this problem,this paper designs a dynamic pricing strategy.In this strategy,service prices of the VEC server and SeV are adjusted dynamically according to the relationship of the supply and demand of computing resources.On this basis,a vehicle collaborative computation offloading scheme is designed to maximize provider's revenue.By transforming the revenue maximization problem of VEC provider under the delay constraint into a multi-user matching problem,the offloading results are obtained using the Kuhn-Munkres(KM)algorithm.Simulation results show that compared to existing strategies,with this dynamic pricing strategy,the prices of the VEC server and SeV can be adjusted dynamically with the supply and demand of resources,so as to maximize the provider's revenue.Compared to existing offloading schemes,this scheme can improve the provider's revenue while meeting task delay.

Key words: Vehicular edge computing, Computation offloading, Collaborative computing, Dynamic pricing

CLC Number: 

  • TN929.5
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