Cellular vehicular-to-everything (C-V2X), a critical Internet of Vehicles (IOV) technology is promised to be enhanced and strengthened to improve road traffic safety and achieve intelligent transportation in the 5G era. However, computation-intensive and latency-sensitive computation tasks of autonomous driving have created a great challenge for computation and storage-limited vehicles. Vehicular edge computing (VEC) is envisioned as a promising approach to processing the explosive computation tasks of vehicular users (VU). In the VEC system, each VU allocates to process partial tasks through offloading and the remaining tasks through local execution. In practical scenarios, the number of vehicles and the arrival of vehicle tasks are random, leading to a highly complex environment for VEC systems. To solve this problem, we propose a novel framework, named LYDDPG, that combines the advantages of Lyapunov optimization and deep reinforcement learning (DRL) to ensure the stability of the system during task offloading.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Lyapunov-guided Deep Reinforcement Learning for Vehicle task Stable offloading


    Beteiligte:
    Huang, Ziyang (Autor:in) / Chen, Yanming (Autor:in) / Zhang, Yiwen (Autor:in)


    Erscheinungsdatum :

    08.05.2024


    Format / Umfang :

    2419313 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Deep Reinforcement Learning Based Task Offloading for UAV-Assisted Edge Computing

    Zhu, Rangang / Huang, Mingxuan / Sun, Kaixuan et al. | IEEE | 2023


    Privacy-Aware Multiagent Deep Reinforcement Learning for Task Offloading in VANET

    Wei, Dawei / Zhang, Junying / Shojafar, Mohammad et al. | IEEE | 2023


    Adaptive task offloading in V2X networks based on deep reinforcement learning

    Yang, Dengsong / Ni, Baili / Qin, Hao et al. | British Library Conference Proceedings | 2022


    Prioritized Task Offloading in Vehicular Edge Computing Using Deep Reinforcement Learning

    Uddin, Ashab / Sakr, Ahmed Hamdi / Zhang, Ning | IEEE | 2024


    Deep Reinforcement Learning for Task Partitioning and Partial Offloading in UAV Networks

    Varasala, Srivikas / Tummala, Veera Manikantha Rayudu / Reddy, Suhas N et al. | IEEE | 2024