Facing the emergence of 6G and the rapid increase in electric vehicles (EVs), smart parking lots providing real-time services like EV charging have become essential. Edge computing, due to its proximity to end devices, offers low latency and high bandwidth, but its limited resources necessitate efficient allocation. We present a parking lots scenario with edge computing system offering four key services: Supply Equipment Communication Controller, charging space detection, monitoring, and video streaming, along with their QoE models and cor-responding estimation models. We predict system requests for the next time slot and employ the Maximum-chosen algorithm and Collaborative Optimal Decision Search method to optimize service deployment and assignment, maximizing QoE values and resource efficiency. Simulation results validate that we can obtain request status that is more similar to real requests by prediction and the Collaborative Optimal Decision Search method can generate optimal service assignment strategy within different methods.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Edge Computing QoE Maximization in EV Parking Scenario


    Contributors:
    Lee, Yu-Chieh (author) / Chiang, Yao (author) / Wei, Hung-Yu (author)


    Publication date :

    2024-06-24


    Size :

    832502 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    edge computing device and method for parking control

    KIM TAE HUN | European Patent Office | 2023

    Free access

    edge computing device and method for parking control

    KIM TAE HUN | European Patent Office | 2023

    Free access


    Autonomous parking system and method based on multi-access edge computing

    ZHOU YI / QIU TIAN / WEI JUNSHENG et al. | European Patent Office | 2021

    Free access

    VEHICLE POSITIONING METHOD AND SYSTEM FOR FIXED PARKING SCENARIO

    ZHANG HENG / ZHANG KAI / DAI JUNYI et al. | European Patent Office | 2025

    Free access