Vehicular fog computing (VFC) that supports inter-vehicular task offloading emerges as a promising complement to handle the explosive growth of computation-intensive tasks in Intelligent Transportation Systems (ITS). Nonetheless, as the fog access points (F-APs) in crowed areas are often overloaded, the conventional single F-AP VFC may become incompetent and energy-inefficient. To tackle the issue, a novel scheme of non-orthogonal multiple access (NOMA)-enabled multi-F-AP VFC with partial offloading is proposed in this work. However, the corresponding energy minimization turns out to be a highly non-trivial non-linear mixed-integer programming problem. To this end, the optimal power allocation is derived by exploiting monotonicity while good task splitting ratio and user association are found through successive convex approximation (SCA)-based interior-point method and game theoretic approach, respectively. Extensive simulations based on MATLAB show that, in the considered scenarios, the proposed scheme can fulfill a more balanced offloading and better exploit the available computing resources, thereby leading to an approximately 30% energy consumption reduction compared to the baselines.


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    Titel :

    Energy-Efficient Cooperative Task Offloading in NOMA-Enabled Vehicular Fog Computing


    Beteiligte:
    Lin, Zhijian (Autor:in) / Chen, Xiaopei (Autor:in) / He, Xiaofan (Autor:in) / Tian, Daxin (Autor:in) / Zhang, Qingsong (Autor:in) / Chen, Pingping (Autor:in)


    Erscheinungsdatum :

    01.07.2024


    Format / Umfang :

    10232381 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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