IoT as a Service. 5th EAI International Conference, IoTaaS 2019, Xi’an, China, November 16-17, 2019, Proceedings

Research Article

A Contract-Based Incentive Mechanism for Resource Sharing and Task Allocation in Container-Based Vehicular Edge Computing

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  • @INPROCEEDINGS{10.1007/978-3-030-44751-9_11,
        author={Siming Wang and Xumin Huang and Beihai Tan and Rong Yu},
        title={A Contract-Based Incentive Mechanism for Resource Sharing and Task Allocation in Container-Based Vehicular Edge Computing},
        proceedings={IoT as a Service. 5th EAI International Conference, IoTaaS 2019, Xi’an, China, November 16-17, 2019, Proceedings},
        proceedings_a={IOTAAS},
        year={2020},
        month={6},
        keywords={Container-based vehicular edge computing Resource sharing Task allocation Contract-based incentive mechanism},
        doi={10.1007/978-3-030-44751-9_11}
    }
    
  • Siming Wang
    Xumin Huang
    Beihai Tan
    Rong Yu
    Year: 2020
    A Contract-Based Incentive Mechanism for Resource Sharing and Task Allocation in Container-Based Vehicular Edge Computing
    IOTAAS
    Springer
    DOI: 10.1007/978-3-030-44751-9_11
Siming Wang1, Xumin Huang1, Beihai Tan1,*, Rong Yu1
  • 1: Guangdong University of Technology
*Contact email: bhtan@gdut.edu.cn

Abstract

Vehicular edge computing (VEC) has emerged as a promising paradigm to provide low-latency service by extending the edge computing to vehicular networks. To meet the ever-increasing demands of computation and communication resources, utilizing vehicles as augmented infrastructure for computation offloading is an appealing idea. However, due to the lack of effective incentive and task allocation mechanism, it is challenging to exploit vehicles as infrastructure for computation offloading. To cope with these challenges, we first propose a container-based VEC paradigm by using efficient, flexible and customized resources of the vehicles. Then, we present a contract-based incentive mechanism to motivate vehicles to share their resources with service requesters (SRs). The optimal contract items are designed for multiple types of vehicles while maximizing the expected utilities of the SRs. Numerical results demonstrate that the proposed contract-based incentive mechanism is efficient compared with conventional schemes.