A Region-based Collaborative Management Scheme for Dynamic Clustering in Green VANET

TL;DR

This paper introduces a region-based collaborative management scheme for dynamic clustering in green VANETs, aiming to improve network efficiency and stability while considering the relationship between connectivity and overlap.

Contribution

It presents a novel joint analysis model and a region-based management scheme that enhances clustering performance in green VANETs by predicting state resemblance.

Findings

Achieves high networking efficiency

Ensures better communication stability

Effectively reduces communication overlap

Abstract

Green Vehicular Ad-hoc Network (VANET) is a newly-emerged research area which focuses on reducing harmful impacts of vehicular communication equipments on the natural environment. Recent studies have shown that grouping vehicles into clusters for green communications in VANETs can significantly improve networking efficiency and reduce infrastructure costs. As a dynamic network system, maintaining the network connectivity and reducing the communication overlap are two critical challenges for green VANET clustering. However, most existing work studies connectivity and overlap separately, lacking a deep understanding of the relationship between them. To address this issue, we present a comprehensive analysis that jointly considers the two critical factors in one model. Specifically, we first design a state resemblance prediction (SRP) model based on the historical trajectory feature relevance between vehicles; Combined with the SRP model, we propose the region-based collaborative management scheme (RCMS) to establish the dynamic clustering; Lastly, we take extensive experiments to verify the region-based collaborative management scheme for dynamic clustering. The results demonstrate that the proposed clustering algorithm can achieve high networking efficiency and better communication stability.