Future perspectives on internet of vehicles resource management: digital twin-enabled edge computing frameworks
Abstract The Internet of Vehicles (IoV) enables advanced developments in automotive systems to communicate with interconnected devices, enhancing traffic flow, security, and utility functions. Edge computing and Digital Twins (DTs) facilitate effective resource management in the IoV. DTs replicate r...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-07-01
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| Series: | Journal of Engineering and Applied Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s44147-025-00692-y |
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| Summary: | Abstract The Internet of Vehicles (IoV) enables advanced developments in automotive systems to communicate with interconnected devices, enhancing traffic flow, security, and utility functions. Edge computing and Digital Twins (DTs) facilitate effective resource management in the IoV. DTs replicate real entities in the virtual domain with real-time control, diagnostics, maintenance, and better management. With edge computing, processing data near the source, these technologies significantly lower response time and optimize system performance. This study provides a comprehensive overview of the latest resource management strategies in DT-enabled edge computing for IoV. Existing approaches are then discussed and compared using clustering, matching, and offloading approaches. Clustering groups of vehicles and devices to manage resources while assigning resources by mapping demand and availability. Offloading techniques delegate computation to edge servers, thereby controlling resources. The paper outlines the strengths and weaknesses of each method, as well as research directions, including the integration of artificial intelligence, security and privacy issues, and interoperability standards. |
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| ISSN: | 1110-1903 2536-9512 |