Computer Science ›› 2021, Vol. 48 ›› Issue (1): 81-88.doi: 10.11896/jsjkx.200800220

Special Issue: Intelligent Edge Computing

• Intelligent Edge Computing • Previous Articles     Next Articles

Computational Task Offloading Scheme Based on Load Balance for Cooperative VEC Servers

YANG Zi-qi, CAI Ying, ZHANG Hao-chen, FAN Yan-fang   

  1. School of Computer,Beijing Information Science & Technology University,Beijing 100101,China
  • Received:2020-08-31 Revised:2020-12-01 Online:2021-01-15 Published:2021-01-15
  • About author:YANG Zi-qi,born in 1996,postgra-duate.Her main research interests include VANETs,MEC and so on.
    CAI Ying,born in 1966,Ph.D,professor,is a member of China Computer Federation.Her main research interests include information security,privacy protection,VANETs and MEC,etc.
  • Supported by:
    National Natural Science Foundation of China(61672106) and Natural Science Foundation of Beijing,China(L192023).

Abstract: In the Vehicular Edge Computing (VEC) network,a large number of computational tasks cannot be processed due to the vehicle's limited computation resource.Therefore,computational tasks generated by on-board applications need to be offloa-ded to the VEC servers for processing.However,the mobility of vehicles and the differences in regional deployment lead to the unbalance among VEC servers,resulting in low computation offloading efficiency and resource utilization.In order to solve the problem,a scheme of computation offloading and resource utilization is proposed to maximize the utility of users.The problem of user utility maximization is decoupled into two subproblems,the VEC server selection decision algorithm based on matching and the joint optimization algorithm for offloading ratio and computation resource allocation based on Adam are proposed to solve the subproblems respectively.After that,the above two algorithms are iterated together until convergence,and the approximate optimal solution is obtained to achieve the load balance.The simulation results show that the proposed scheme can effectively decrease the processing delay of computational tasks,save vehicle's energy,enhance the vehicle utility,and perform well on load balance compared to the nearest offloading scheme and the predictive offloading scheme.

Key words: Adam algorithm, Computation offloading, Load balancing, Matching algorithm, Resource allocation, Vehicular edge computing

CLC Number: 

  • TN929.5
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