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Towards a Resource-Aware K-Selection Model for Optimizing V2X Communication in Autonomous Vehicles

Authors:
Olanrewaju Ahmed
David Grace
Kayode Popoola

Keywords: Cluster; bandwidth; V2X; V2V; sidelink.

Abstract:
The rise of autonomous vehicles is accompanied by the emergence of bandwidth-intensive applications like real-time 3D map downloads, necessitating improved bandwidth utilization. While clustering has proven effective in prior research to partially address this challenge, existing works often assume a perfect cluster formation without accounting for outliers, and the selection of the number of clusters (k) tends to be resource-agnostic. This paper presents the preliminary findings from the initial cluster analysis phase, laying the foundation for a resource-aware k-selection model. This model aims to optimize bandwidth resources and alleviate throughput bottlenecks between Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) links. The cluster analysis part of our work examines the variation in sizes of various vehicular cluster components concerning changes in cluster range (dth) and the number of clusters (k). Notably, our approach considers unclustered vehicles, acknowledging their impact on bandwidth utilization. Our results reveal a consistent pattern and correlation between the size of different vehicular components and the variables considered (k and dth). Drawing insights from this understanding of vehicular cluster behaviour, we propose an approach to optimize V2I and V2V bandwidth usage while minimizing throughput bottlenecks between V2V and V2I links. This resource-aware k-selection model holds the potential to significantly enhance the efficiency and performance of Vehicle-to-Everything (V2X) communication in the era of autonomous vehicles, contributing to the realization of a seamless and high-throughput vehicular communication network.

Pages: 15 to 20

Copyright: Copyright (c) IARIA, 2024

Publication date: March 10, 2024

Published in: conference

ISSN: 2327-2058

ISBN: 978-1-68558-134-3

Location: Athens, Greece

Dates: from March 10, 2024 to March 14, 2024