An Adaptive Vehicle Clustering Algorithm Based on Power Minimization in Vehicular Ad-Hoc Networks

Haitao Zhao, Jiawen Tang, Bamidele Adebisi, Tomoaki Ohtsuki, Guan Gui, Hongbo Zhu

研究成果: Article査読

抄録

In this paper, we propose an adaptive vehicle clustering algorithm based on fuzzy C-means algorithm, which aims at minimizing power consumption of the vehicles. Specifically, the proposed algorithm firstly dynamically allocates the computing resources of each virtual machine in the vehicle, according to the popularity of different virtualized network functions. The optimal clustering number to minimize the total energy consumption of vehicles is determined using the fuzzy C-means algorithm and the clustering head is selected based on vehicles moving direction, weighted mobility, and entropy. Simulation results are provided to confirm that the proposed algorithm can decrease the power consumption of vehicles while satisfying the vehicle delay requirement.

本文言語English
ページ(範囲)2939-2948
ページ数10
ジャーナルIEEE Transactions on Vehicular Technology
71
3
DOI
出版ステータスPublished - 2022 3月 1

ASJC Scopus subject areas

  • 自動車工学
  • 航空宇宙工学
  • 電子工学および電気工学
  • 応用数学

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