A context-aware edge-based VANET communication scheme for ITS

Chang An (Corresponding Author), Celimuge Wu (Corresponding Author), Tsutomu Yoshinaga, Xianfu Chen, Yusheng Ji

    Research output: Contribution to journalArticleScientificpeer-review

    6 Citations (Scopus)

    Abstract

    We propose a context-aware edge-based packet forwarding scheme for vehicular networks. The proposed scheme employs a fuzzy logic-based edge node selection protocol to find the best edge nodes in a decentralized manner, which can achieve an efficient use of wireless resources by conducting packet forwarding through edges. A reinforcement learning algorithm is used to optimize the last two-hop communications in order to improve the adaptiveness of the communication routes. The proposed scheme selects different edge nodes for different types of communications with different context information such as connection-dependency (connection-dependent or connection-independent), communication type (unicast or broadcast), and packet payload size. We launch extensive simulations to evaluate the proposed scheme by comparing with existing broadcast protocols and unicast protocols for various network conditions and traffic patterns.

    Original languageEnglish
    Article number2022
    JournalSensors
    Volume18
    Issue number7
    DOIs
    Publication statusPublished - 1 Jul 2018
    MoE publication typeA1 Journal article-refereed

    Keywords

    • Broadcast communications
    • Context-aware communications
    • Edge computing
    • Intelligent transportation systems
    • Unicast communications
    • VANET
    • Vehicular networks

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