Vehicular edge computing (VEC), as an emerging computing paradigm, enables the timely processing of computing tasks at the network edge through on-vehicle servers, thereby meeting users’ demands for information freshness. In this paper, we introduce the Age of Information (AoI) to measure information freshness and investigate the scheduling problem minimizing the long-term average AoI in VEC-assisted Internet of Things systems. The main challenge lies in the strong coupling between link scheduling and server selection under the location constraints of VEC. To address this issue, we design a scheduling strategy based on deep reinforcement learning and improve the neural network structure using a branch network approach, reducing complexity by decreasing the number of actions represented in the network’s output layer. Moreover, we introduce an action masking scheme that accelerates the algorithm’s convergence in this system. Numerical results show that the proposed scheduling algorithm can achieve up to a 25.4% performance gain compared to existing advanced algorithms.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Scheduling for Maximizing the Information Freshness in Vehicular Edge Computing- Assisted IoT Systems


    Contributors:
    Xie, Xin (author) / Zhong, Tao (author) / Wang, Heng (author)


    Publication date :

    2025-03-01


    Size :

    1797449 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    LEO Satellite-Assisted Vehicular Edge Computing

    Li, Caiguo / Shang, Bodong / Feng, Jie et al. | IEEE | 2023


    Information freshness-aware task offloading in air-ground integrated edge computing systems

    Chen, X. (Xianfu) / Wu, C. (Celimuge) / Chen, T. (Tao) et al. | BASE | 2022

    Free access

    Efficient Pareto Optimality-based Task Scheduling for Vehicular Edge Computing

    Da Costa, Joahannes B. D. / de Souza, Allan M. / Rosario, Denis et al. | IEEE | 2022


    URLLC Resource Slicing and Scheduling in 5G Vehicular Edge Computing

    Hao, Min / Ye, Dongdong / Wang, Siming et al. | IEEE | 2021


    Mobility and Deadline-Aware Task Scheduling Mechanism for Vehicular Edge Computing

    da Costa, Joahannes B. D. / de Souza, Allan M. / Meneguette, Rodolfo I. et al. | IEEE | 2023

    Free access