In the Internet of Vehicles (IoV) applications, vehicle and in-vehicle users need to process computation-intensive and latency-sensitive tasks. Offloading tasks to satellite edge servers can alleviate the computational burden and reduce vehicular users' energy consumption, especially in remote areas. In this paper, we study a low earth orbit (LEO) satellite-assisted vehicular edge computing system. We jointly consider user association variable, task allocation, power control, and bandwidth allocation to minimize weighted sum-energy consumption in the system. Specifically, we design an iterative optimization algorithm, which decomposes the original non-convex problem into several sub-problems. We solve each sub-problem efficiently using variable substitutions, and the Karush-Kuhn-Tucke (KKT) condition. Simulation results show that the proposed algorithm has a good convergence performance and effectively reduces system weighted sum-energy consumption compared to benchmarks.


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    Titel :

    LEO Satellite-Assisted Vehicular Edge Computing


    Beteiligte:
    Li, Caiguo (Autor:in) / Shang, Bodong (Autor:in) / Feng, Jie (Autor:in) / Chen, Shanzhi (Autor:in)


    Erscheinungsdatum :

    24.11.2023


    Format / Umfang :

    798615 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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