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A scalable blockchain storage scheme for VANET.

Authors :
Wei, Wenxiang
Zhu, Nafei
Wang, Jian
Song, Hongyu
He, Jingsha
Source :
Cluster Computing; Jul2024, Vol. 27 Issue 4, p3957-3981, 25p
Publication Year :
2024

Abstract

Intelligent transportation systems (ITSs) make it possible for applications such as autonomous driving, active safety systems and smart cities. As the infrastructure of ITSs, vehicular ad-hoc network (VANET) plays a key role in ensuring traffic safety while improving driving experience and comfort. However, VANET faces many challenges as the network is exposed to the public and involves sensitive information such as vehicle control commands and driving records. Although blockchain technology can provide such features as decentralization, immutability, non-reliance on trust and traceability, most of the existing blockchain systems impose high storage and computing capacity requirements for participating nodes while terminals nodes in VANET, such as road-side units (RSUs), on-board units (OBUs) and sensors, usually have very limited storage and computing capacity. To solve this problem, this paper proposes a blockchain system that provides scalable storage capacity for VANETs. The proposed scheme uses network sharding and multi-consensus strategy to improve the topology and consensus process of the blockchain. Aimed at lowering the storage requirement on the RSU nodes that participate in the blockchain, a collaborative storage mechanism and a dynamic copy number strategy for the blockchain ledger is designed. Experimental results show that compared to existing schemes, the proposed scalable blockchain storage scheme can significantly lower the storage requirement for the blockchain nodes, thus making it possible for the nodes with limited storage capacity in VANET to participate in the maintenance of the blockchain to prevent the blockchain from drifting towards centralization, and support maximal sharing of road traffic information while ensuring the security, privacy and trustworthiness of information. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13867857
Volume :
27
Issue :
4
Database :
Complementary Index
Journal :
Cluster Computing
Publication Type :
Academic Journal
Accession number :
178805431
Full Text :
https://doi.org/10.1007/s10586-023-04238-w