Spatial Intelligence toward Trustworthy Vehicular IoT

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

研究成果: Article査読

70 被引用数 (Scopus)

抄録

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.

本文言語English
論文番号8493113
ページ(範囲)22-27
ページ数6
ジャーナルIEEE Communications Magazine
56
10
DOI
出版ステータスPublished - 2018 10月
外部発表はい

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学

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