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author:

Guo, Zhaohui (Guo, Zhaohui.) [1] | Liu, Qiang (Liu, Qiang.) [2] | Gao, Zhen (Gao, Zhen.) [3] | Liu, Lei (Liu, Lei.) [4] | Gong, Yi (Gong, Yi.) [5] | Liu, Ximeng (Liu, Ximeng.) [6] | Kumar, Neeraj (Kumar, Neeraj.) [7] | Guizani, Mohsen (Guizani, Mohsen.) [8]

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EI

Abstract:

Asan emerging distributed ledger technology, blockchain provides multi-party trust between unreliable devices to share data and resources cooperatively, which facilitates the Internet of Vehicles (IoVs) applications. In the typical blockchain-enabled IoV (BIoV) scenarios, based on the data of common interest collected by various sensors, the IoV devices jointly maintain the world state in the form of address-balance pairs as the proof for transaction issuing and validation, where Ethereum-like blockchain is used as the finite-state machine driven by the transactions. However, with the extension of the IoV network, an enormous number of accounts leads to the explosive growth of the state data, which has been the main challenge for BIoV with resource-limited devices. This paper proposes a modular-based adaptive bit-width compression (ABC) scheme to reduce the state data storage on each device by representing the address as a remainder with a shorter bit-width. Besides, a new transaction validation method is designed with the support of the XOR filter, which guarantees that the core functions of the blockchain can still be performed normally with the proposed scheme applied. Theoretical analysis and simulation results show that the compression ratio for the address data could be more than 80%, which dramatically improves the scalability of BIoV system. In addition, the extra privacy-preserving property is introduced with the compression scheme because the account information is unrecoverable from the remainders. © 1967-2012 IEEE.

Keyword:

Binary sequences Blockchain Data privacy Digital storage Distributed ledger Real time systems Scalability Smart contract

Community:

  • [ 1 ] [Guo, Zhaohui]Tianjin University, School of Microelectronics, Tianjin; 300072, China
  • [ 2 ] [Liu, Qiang]Tianjin University, School of Microelectronics, Tianjin; 300072, China
  • [ 3 ] [Gao, Zhen]Tianjin University, School of Electrical and Information Engineering, Tianjin; 300072, China
  • [ 4 ] [Liu, Lei]Xidian University, Guangzhou Institute of Technology, Guangzhou; 510555, China
  • [ 5 ] [Liu, Lei]Qilu University of Technology, Shandong Academy of Sciences, Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Jinan; 250014, China
  • [ 6 ] [Gong, Yi]Beijing Information Science and Technology University, Department of Information and Telecommunication Engineering, Beijing; 10010, China
  • [ 7 ] [Liu, Ximeng]Fuzhou University, College of Computer and Data Science, Fuzhou; 350116, China
  • [ 8 ] [Kumar, Neeraj]Thapar Institute of Engineering and Technology, CSED, Patiala; 147004, India
  • [ 9 ] [Kumar, Neeraj]UEHS, Warszawa; 01-043, Poland
  • [ 10 ] [Guizani, Mohsen]Mohamed Bin Zayed University of Artificial Intelligence, Department of Machine Learning, Masdar; 999041, United Arab Emirates

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Source :

IEEE Transactions on Vehicular Technology

ISSN: 0018-9545

Year: 2024

Issue: 10

Volume: 73

Page: 15567-15583

6 . 1 0 0

JCR@2023

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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