Computation Resource Allocation and Task Assignment Optimization in Vehicular Fog Computing: A Contract-Matching Approach

Zhenyu Zhou, Pengju Liu, Junhao Feng, Yan Zhang, Shahid Mumtaz, Jonathan Rodriguez

    Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

    18 Wedi eu Llwytho i Lawr (Pure)

    Crynodeb

    Vehicular fog computing (VFC) has emerged as a promising solution to relieve the overload on the base station and reduce the processing delay during the peak time. The computation tasks can be offloaded from the base station to vehicular fog nodes by leveraging the under-utilized computation resources of nearby vehicles. However, the wide-area deployment of VFC still confronts several critical challenges such as the lack of efficient incentive and task assignment mechanisms. In this paper, we address the above challenges and provide a solution to minimize the network delay from a contract-matching integration perspective. First, we propose an efficient incentive mechanism
    based on contract theoretical modeling. The contract is tailored for the unique characteristic of each vehicle type to maximize the expected utility of the base station. Next, we transform the task assignment problem into a two-sided matching problem between vehicles and user equipments (UEs). The formulated problem is solved by a pricing-based stable matching algorithm which iteratively carries out the “propose” and “price-rising” procedures to derive a stable matching based on the dynamically updated preference lists. Finally, numerical results demonstrate that significant performance improvement can be achieved by the proposed scheme.
    Iaith wreiddiolSaesneg
    Tudalennau (o-i)3113-3125
    CyfnodolynIEEE Transactions on Vehicular Communications
    Cyfrol68
    Rhif cyhoeddi4
    Dyddiad ar-lein cynnar23 Ion 2019
    Dynodwyr Gwrthrych Digidol (DOIs)
    StatwsE-gyhoeddi cyn argraffu - 23 Ion 2019

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