Data storage and sharing for the internet of vehicles and GPBFT consensus algorithm

This study constructs a secure and efficient data storage and sharing architecture for the Internet of Vehicles. A practical Byzantine fault-tolerant consensus algorithm using reputation was proposed to address the shortcomings of roadside unit equipment in the architecture. The experimental results showed that in the performance verification of reinforced data storage, the storage proportion of the research scheme was always lower than that of the comparison algorithm. In the simulated 5000 transactions, it was always lower than 40 MB, while the comparison algorithm reached a maximum of 72 MB. The efficiency of querying registration information and vehicle data increased by 38.2% and 49.1%, respectively. In the shared performance verification, the fully loaded roadside unit devices decreased by a maximum of 2.8%. Under heavy load conditions, the fully loaded nodes decreased by a maximum of 20.7%. In the validation of the proposed consensus algorithm, its performance was more stable in terms of throughput, and the number of transactions processed per second by d (10) remained basically between 380 and 640. Overall, the constructed secure and efficient data storage and sharing architecture for the Internet of Vehicles is efficient and secure, which can be effectively applied in practical IoV systems.

Authors

Institutions

Publication Details

Journal
International Journal of Vehicle Information and Communication Systems
Published
2025-12-18
DOI
https://doi.org/10.1504/ijvics.2026.150584
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

Data storage and sharing for the internet of vehicles and GPBFT consensus algorithm

Jiyan Zhou, Jinfeng Liu
International Journal of Vehicle Information and Communication Systems
Vehicular Ad Hoc Networks (VANETs)
article

Data storage and sharing for the internet of vehicles and GPBFT consensus algorithm

Jiyan Zhou, Jinfeng Liu
article en

Abstract

This study constructs a secure and efficient data storage and sharing architecture for the Internet of Vehicles. A practical Byzantine fault-tolerant consensus algorithm using reputation was proposed to address the shortcomings of roadside unit equipment in the architecture. The experimental results showed that in the performance verification of reinforced data storage, the storage proportion of the research scheme was always lower than that of the comparison algorithm. In the simulated 5000 transactions, it was always lower than 40 MB, while the comparison algorithm reached a maximum of 72 MB. The efficiency of querying registration information and vehicle data increased by 38.2% and 49.1%, respectively. In the shared performance verification, the fully loaded roadside unit devices decreased by a maximum of 2.8%. Under heavy load conditions, the fully loaded nodes decreased by a maximum of 20.7%. In the validation of the proposed consensus algorithm, its performance was more stable in terms of throughput, and the number of transactions processed per second by d (10) remained basically between 380 and 640. Overall, the constructed secure and efficient data storage and sharing architecture for the Internet of Vehicles is efficient and secure, which can be effectively applied in practical IoV systems.

International Journal of Vehicle Information and Communication SystemsVol. 11(1)
Guangdong Polytechnic of Science and Technology (CN)
Openalex Percentile: Top 59%
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.