Secure and Personalized Edge Computing Services in 6G Heterogeneous Vehicular Networks
Abstract
The customization of edge computing services is one of the key research fields in sixth-generation (6G) heterogeneous vehicular networks (HetVNETs). With various personalized requirements of vehicles on computation-intensive applications, how to explore the heterogeneous computing resources in the 6G HetVNETs to guarantee vehicles with the customized Quality of Experience (QoE), therefore, becomes a challenge. In this article, we develop a novel secure scheme to provide personalized edge computing services for moving vehicles (MVs) in 6G HetVNETs. In the scheme, a smart-contract-based secure edge computing architecture is designed by jointly considering the attack models and the characteristics of the 6G network infrastructures (e.g., satellites, drones, base stations, and roadside units), where each network infrastructure manages a number of parking vehicles to complete computing services collaboratively. With this architecture, based on the available computing resources owned by different network infrastructures, the collaborative computing resource allocation algorithm is designed to help each network infrastructure decide a customized service strategy (CSS) to satisfy the QoE of MVs. After deciding the CSSs, a model based on the second price-sealed auction is formulated to describe the competition among the network infrastructures, where the Nash equilibrium of the game is obtained to guide their optimal bidding strategies to obtain the chance for completing the services. The security analysis and the simulation results show that the proposed scheme can defend against the attacks and lead to a lower cost for completing the services than the conventional schemes.
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Exploring the integration of edge computing units in vehicles proves beneficial for handling computation-intensive tasks and minimizing latency.
“Exploring the integration of edge computing units in vehicles proves beneficial for handling computation-intensive tasks and minimizing latency.”
From Towards 6G V2X Sidelink: Survey of Resource Allocation—Mathematical Formulations, Challenges, and Proposed Solutions (2024) · cites this paper as [140]
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Flizikowski, A., Alkhovik, E., Mowla, M. M., & Rahman, M. A. (2022) · IEEE Conference on Standards for Communications and Networking · doi:10.1109/cscn57023.2022.10051118 · Cited by 3 · see citing works
Lightweight Authenticated Task Offloading in 6G-Cloud Vehicular Twin Networks
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Futuristic Trends Toward Connected Autonomous Vehicles in Hybrid Vehicular Networks
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Self-citation
- Authors
- Hui, Y., Cheng, N., Su, Z., Huang, Y., Zhao, P., Luan, T. H., & Li, C.
- Affiliations
- Xidian University (CN)
- Shanghai University (CN)
- Venue
- IEEE Internet of Things Journal
- Published
- 2022-04-15
- Volume
- 9
- Issue
- 8
- Pages
- 5920-5931
- ISSN
- 2327-4662 (ISSN-L)
- 2372-2541
- OpenAlex
- W3136002755
- Cited by
- 76
- References
- 39
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 12 · 2023: 29 · 2022: 18 · 2021: 8
- FWCI
- 7.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Internet of Things Journal (publishedVersion)
- Funders
- National Key Research and Development Program of China (2020YFB1807700)
- National Natural Science Foundation of China (62071356, 61901341, U1808207, 91746114)
- Fundamental Research Funds for the Central Universities of Ministry of Education of China (XJS200109, JB210113)
- Xi'an Science and Technology Association (095920201322)
- National Natural Science Foundation of Shaanxi Province (2020JQ-301)
- Higher Education Discipline Innovation Project (D18003)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Keywords
- personalized services, smart contracts, moving vehicles, Nash equilibrium, bidding strategy, quality of experience
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