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DPNVC: A novel density-based probability VANET caching framework built upon the NDN

journal contribution
posted on 2025-11-04, 10:30 authored by Yuanchen LiYuanchen Li, Lin GuanLin Guan, Ziyang Zhang, George VogiatzisGeorge Vogiatzis
<p dir="ltr">Vehicular Ad Hoc Networks (VANETs) are an important component of modern network systems, supporting applications such as real-time entertainment, traffic notifications, and emergency services. However, the highly dynamic and rapidly changing topology of VANETs presents serious challenges for conventional data retrieval mechanisms designed for Mobile Ad Hoc Networks (MANETs), resulting in degraded performance. To address this issue, a novel Density-Based Probability VANET Caching Framework Built Upon the Named Data Networking (NDN) was proposed, namely DPNVC. This original framework dynamically calculates caching probabilities based on local traffic density, enabling to adapt to frequent topology changes. Additionally, the NDN communication model is applied to effectively suppress redundant packet forwarding in VANET environments. Empirical simulation results show that DPNVC significantly enhances Quality of Service (QoS) in various scenarios, including urban, highway, and city settings. Compared to baseline methods, it reduces link load by up to 25 %, decreases data retrieval time by up to 30 %, and improves the local satisfaction ratio by up to 66 %. It also maintains a competitive one-hop hit ratio performance.</p>

History

School

  • Science

Department

  • Computer Science

Published in

Simulation Modelling Practice and Theory

Volume

146

Publisher

Elsevier B.V.

Version

  • AM (Accepted Manuscript)

Rights holder

© Elsevier B.V.

Publisher statement

This accepted manuscript version is made available under the CC-BY-NC-ND 4.0 licence https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2025-10-24

Publication date

2025-10-31

Copyright date

2025

ISSN

1569-190X

eISSN

1878-1462

Language

  • en

Depositor

Yuanchen Li. Deposit date: 31 October 2025

Article number

103218

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