Digital Retina for IoV Towards 6G: Architecture, Opportunities, and Challenges
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866913191371472896 |
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| author | Zheng, Kan Mei, Jie Yang, Haojun Hou, Lu Ma, Siwei |
| author_facet | Zheng, Kan Mei, Jie Yang, Haojun Hou, Lu Ma, Siwei |
| contents | Vehicles are no longer isolated entities in traffic environments, thanks to the development of IoV powered by 5G networks and their evolution into 6G. However, it is not enough for vehicles in a highly dynamic and complex traffic environment to make reliable and efficient decisions. As a result, this paper proposes a cloud-edge-end computing system with multi-streams for IoV, referred to as Vehicular Digital Retina (VDR). Local computing and edge computing are effectively integrated in the VDR system through the aid of vehicle-to-everything (V2X) networks, resulting in a heterogeneous computing environment that improves vehicles' perception and decision-making abilities with collaborative strategies. Once the system framework is presented, various important functions in the VDR system are explained in detail, including V2X-aided collaborative perception, V2X-aided stream sharing for collaborative learning, and V2X-aided secured collaboration. All of them enable the development of efficient mechanisms of data sharing and information interaction with high security for collaborative intelligent driving. We also present a case study with simulation results to demonstrate the effectiveness of the proposed VDR system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_04916 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Digital Retina for IoV Towards 6G: Architecture, Opportunities, and Challenges Zheng, Kan Mei, Jie Yang, Haojun Hou, Lu Ma, Siwei Networking and Internet Architecture Vehicles are no longer isolated entities in traffic environments, thanks to the development of IoV powered by 5G networks and their evolution into 6G. However, it is not enough for vehicles in a highly dynamic and complex traffic environment to make reliable and efficient decisions. As a result, this paper proposes a cloud-edge-end computing system with multi-streams for IoV, referred to as Vehicular Digital Retina (VDR). Local computing and edge computing are effectively integrated in the VDR system through the aid of vehicle-to-everything (V2X) networks, resulting in a heterogeneous computing environment that improves vehicles' perception and decision-making abilities with collaborative strategies. Once the system framework is presented, various important functions in the VDR system are explained in detail, including V2X-aided collaborative perception, V2X-aided stream sharing for collaborative learning, and V2X-aided secured collaboration. All of them enable the development of efficient mechanisms of data sharing and information interaction with high security for collaborative intelligent driving. We also present a case study with simulation results to demonstrate the effectiveness of the proposed VDR system. |
| title | Digital Retina for IoV Towards 6G: Architecture, Opportunities, and Challenges |
| topic | Networking and Internet Architecture |
| url | https://arxiv.org/abs/2401.04916 |