Smart Contract-Based Decentralized Data Sharing and Content Delivery for Intelligent Connected Vehicles in Edge Computing

Li, C; Zhang, Y; Wu, J; Luo, Y; Yu, S

Smart Contract-Based Decentralized Data Sharing and Content Delivery for Intelligent Connected Vehicles in Edge Computing

Li, C Zhang, Y Wu, J Luo, Y Yu, S

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Intelligent Transportation Systems, 2024, PP, (99)
Issue Date:: 2024-01-01

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Field	Value	Language
dc.contributor.author	Li, C
dc.contributor.author	Zhang, Y
dc.contributor.author	Wu, J
dc.contributor.author	Luo, Y
dc.contributor.author	Yu, S https://orcid.org/0000-0003-4485-6743
dc.date.accessioned	2024-08-07T05:26:16Z
dc.date.available	2024-08-07T05:26:16Z
dc.date.issued	2024-01-01
dc.identifier.citation	IEEE Transactions on Intelligent Transportation Systems, 2024, PP, (99)
dc.identifier.issn	1524-9050
dc.identifier.issn	1558-0016
dc.identifier.uri	http://hdl.handle.net/10453/180312
dc.description.abstract	Intelligent Connected Vehicles (ICVs) need to obtain real-time traffic data from nearby ICVs or remote content providers to ensure safe driving. However, providers are hesitant to share their data due to privacy and benefits concerns. To ensure privacy while improving efficiency of obtaining data, we proposed smart contract-based data sharing among ICVs, and content delivery between ICVs and remote content provider. To solve low willingness to vehicles due to untrustworthy third-party platforms, we use smart contracts to implement access control during data upload and transaction. Then, we propose a one-to-many sharing model based on Stackelberg game to model the interaction between consumers and owners. Consumers adjust their reward strategies with the owners’ optimal strategies to maximize its utility, thus obtaining the nash equilibrium solution. To provide reliable quality of service (QoS) and security guarantee for content delivery, smart contracts regulate the delivery process, facilitating automatic execution under specific conditions. Transaction records audited and stored on blockchain enhance transparency and trustworthiness. Utilizing a delivery utility model that considers benefits, costs, and mining profits, proposed quantum particle swarm optimization (QPSO) algorithm is used to find the optimal solution. We built an EdgeChain testbed, and used BDD-100K dataset to evaluate the performance in utility, access delay, etc. Compared to CTM and MFPA, proposed data sharing algorithm achieves maximum consumer utility. Compared to LRU, PCCM and MARL, when content is 400, proposed content delivery algorithm reduces average access delay by 30.88%, 18.92% and 4.86%, and reduce backhaul load by 50.04%, 47.23% and 3.16%.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Transactions on Intelligent Transportation Systems
dc.relation.isbasedon	10.1109/TITS.2024.3388422
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 0905 Civil Engineering, 1507 Transportation and Freight Services
dc.subject.classification	Logistics & Transportation
dc.subject.classification	3509 Transportation, logistics and supply chains
dc.subject.classification	4602 Artificial intelligence
dc.subject.classification	4603 Computer vision and multimedia computation
dc.title	Smart Contract-Based Decentralized Data Sharing and Content Delivery for Intelligent Connected Vehicles in Edge Computing
dc.type	Journal Article
utslib.citation.volume	PP
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0905 Civil Engineering
utslib.for	1507 Transportation and Freight Services
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	University of Technology Sydney/Strength - CCSP - Centre for Cyber Security and Privacy
utslib.copyright.status	closed_access	*
dc.date.updated	2024-08-07T05:26:14Z
pubs.issue	99
pubs.publication-status	Published
pubs.volume	PP
utslib.citation.issue	99

Abstract:

Intelligent Connected Vehicles (ICVs) need to obtain real-time traffic data from nearby ICVs or remote content providers to ensure safe driving. However, providers are hesitant to share their data due to privacy and benefits concerns. To ensure privacy while improving efficiency of obtaining data, we proposed smart contract-based data sharing among ICVs, and content delivery between ICVs and remote content provider. To solve low willingness to vehicles due to untrustworthy third-party platforms, we use smart contracts to implement access control during data upload and transaction. Then, we propose a one-to-many sharing model based on Stackelberg game to model the interaction between consumers and owners. Consumers adjust their reward strategies with the owners’ optimal strategies to maximize its utility, thus obtaining the nash equilibrium solution. To provide reliable quality of service (QoS) and security guarantee for content delivery, smart contracts regulate the delivery process, facilitating automatic execution under specific conditions. Transaction records audited and stored on blockchain enhance transparency and trustworthiness. Utilizing a delivery utility model that considers benefits, costs, and mining profits, proposed quantum particle swarm optimization (QPSO) algorithm is used to find the optimal solution. We built an EdgeChain testbed, and used BDD-100K dataset to evaluate the performance in utility, access delay, etc. Compared to CTM and MFPA, proposed data sharing algorithm achieves maximum consumer utility. Compared to LRU, PCCM and MARL, when content is 400, proposed content delivery algorithm reduces average access delay by 30.88%, 18.92% and 4.86%, and reduce backhaul load by 50.04%, 47.23% and 3.16%.

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