Spatial Intelligence toward Trustworthy Vehicular IoT

Celimuge Wu, Zhi Liu, Di Zhang, Tsutomu Yoshinaga, Yusheng Ji

    研究成果: Article

    24 引用 (Scopus)

    抜粋

    Spatial challenges for the vehicular Internet of Things come from mobility, high density, sparse connectivity, and heterogeneity. In this article, we propose two techniques, namely decentralized moving edge and multi-tier multi-access edge clustering, to handle these challenges. The vehicle as an edge concept of the decentralized moving edge provides a more suitable solution to meet the throughput and latency performance requirements by conducting distributed communication, data caching, and computing tasks at vehicles. Multi-tier multi-access edge clustering generates different levels of clusters for more efficient integration of different types of access technologies including licensed/unlicensed long-range low-throughput communications and unlicensed short-range high-throughput communications. We employ fuzzy logic to jointly consider multiple inherently contradictory metrics and use Q-learning to achieve a self-evolving capability. Realistic computer simulations are conducted to show the advantage of the proposed protocols over alternatives.

    元の言語English
    記事番号8493113
    ページ(範囲)22-27
    ページ数6
    ジャーナルIEEE Communications Magazine
    56
    発行部数10
    DOI
    出版物ステータスPublished - 2018 10 1

      フィンガープリント

    ASJC Scopus subject areas

    • Computer Science Applications
    • Computer Networks and Communications
    • Electrical and Electronic Engineering

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