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

Zhao, Haito ORCID: https://orcid.org/0000-0002-3539-3532, Tang, Jiawen, Adebisi, Bamidele ORCID: https://orcid.org/0000-0001-9071-9120, Ohtsuki, Tomoaki ORCID: https://orcid.org/0000-0003-3961-1426, Gui, Guan ORCID: https://orcid.org/0000-0003-3888-2881 and Zhu, Hongbo ORCID: https://orcid.org/0000-0002-1032-4434 (2022) An Adaptive Vehicle Clustering Algorithm Based on Power Minimization in Vehicular Ad-Hoc Networks. IEEE Transactions on Vehicular Technology, 71 (3). pp. 2939-2948. ISSN 0018-9545

Preview

Accepted Version Available under License In Copyright. Download (971kB) | Preview

Abstract

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.