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Communications and Networking. 15th EAI International Conference, ChinaCom 2020, Shanghai, China, November 20-21, 2020, Proceedings

Research Article

A Computation Offloading Strategy Based on Stackelberg Game for Vehicular Network

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  • @INPROCEEDINGS{10.1007/978-3-030-67720-6_35,
        author={Yingdi Dai and Zhanjun Liu and Ya Kang},
        title={A Computation Offloading Strategy Based on Stackelberg Game for Vehicular Network},
        proceedings={Communications and Networking. 15th EAI International Conference, ChinaCom 2020, Shanghai, China, November 20-21, 2020,  Proceedings},
        proceedings_a={CHINACOM},
        year={2021},
        month={2},
        keywords={Vehicular network Computation offloading Stackelberg game},
        doi={10.1007/978-3-030-67720-6_35}
    }
    
  • Yingdi Dai
    Zhanjun Liu
    Ya Kang
    Year: 2021
    A Computation Offloading Strategy Based on Stackelberg Game for Vehicular Network
    CHINACOM
    Springer
    DOI: 10.1007/978-3-030-67720-6_35
Yingdi Dai1,*, Zhanjun Liu1, Ya Kang1
  • 1: School of Communication and Information Engineering
*Contact email: dongnan163@163.com

Abstract

Edge computing was proposed to offload the computing tasks of the vehicle to the vehicle fog nodes, which can achieve efficient vehicle services and higher utilization of computing resources. However, encouraging vehicles to share resources or execute applications for others remains a sensitive issue due to the selfishness of users. In this paper, we propose an incentive mechanism based on Stackelberg game and the problem of computation offloading of tasks on vehicles is modeled. In order to utilize the idle computing resources of nearby vehicles, for the computation offloading in vehicular networks. Specifically, we introduce multi-hop offloading into vehicle-to-vehicle (V2V) offloading, and model the probability of forwarding packets by assisting vehicles from multiple perspectives in order to ensure the stability and reliability of communication transmission. A distributed iterative algorithm is designed to solve the final Stackelberg equilibrium, so as to minimize the cost of requesting vehicles to execute tasks and maximize the service benefits of assisting vehicles. The simulation results show that the proposed computation offloading strategy has superiorities in improving utilization efficiency, reducing tasks execution latency and enhancing service quality.

Keywords
Vehicular network Computation offloading Stackelberg game
Published
2021-02-02
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-67720-6_35
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