DPN: Density-Based Probability VANET Caching Method Leveraging with NDN Concept

Vehicular Ad Hoc Network (VANET) is expected to have broad applications, such as traffic warnings and accident rescue. However, the highly dynamic nature of VANET topology challenges conventional Mobile Ad-hoc Network (MANET) data retrieval mecha-nisms, causing significant performance degradation. To address this, we propose a novel caching mechanism that leverages density-based probability caching and incorpo-rates Named Data Networking (NDN). This approach aims to improve the Quality of Service (QoS) in VANET, especially in high-traffic urban environments, by dynam-ically adapting to topology changes and uneven traffic density. Empirical experiments show that our proposed mechanism surpasses existing benchmarks in latency and link load metrics while maintaining a competitive cache hit ratio.

Authors

Institutions

Publication Details

Published
2024-09-23
DOI
https://doi.org/10.1109/mass62177.2024.00088
Primary Topic
Vehicular Ad Hoc Networks (VANETs)
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DPN: Density-Based Probability VANET Caching Method Leveraging with NDN Concept

George Vogiatzis, Lin Guan, Ziyang Zhang, Yuanchen Li
Vehicular Ad Hoc Networks (VANETs)
article

DPN: Density-Based Probability VANET Caching Method Leveraging with NDN Concept

George Vogiatzis, Lin Guan, Ziyang Zhang, Yuanchen Li
article en

Abstract

Vehicular Ad Hoc Network (VANET) is expected to have broad applications, such as traffic warnings and accident rescue. However, the highly dynamic nature of VANET topology challenges conventional Mobile Ad-hoc Network (MANET) data retrieval mecha-nisms, causing significant performance degradation. To address this, we propose a novel caching mechanism that leverages density-based probability caching and incorpo-rates Named Data Networking (NDN). This approach aims to improve the Quality of Service (QoS) in VANET, especially in high-traffic urban environments, by dynam-ically adapting to topology changes and uneven traffic density. Empirical experiments show that our proposed mechanism surpasses existing benchmarks in latency and link load metrics while maintaining a competitive cache hit ratio.

Loughborough University (GB)
Openalex Percentile: Top 83%
Vehicular Ad Hoc Networks (VANETs)
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.