Semantic Scholar Open Access 2023 76 sitasi

Smart Traffic Navigation System for Fault-Tolerant Edge Computing of Internet of Vehicle in Intelligent Transportation Gateway

Shuangming Yang Jiangtong Tan Tao Lei B. Linares‐Barranco

Abstrak

To investigate the diversified technologies in Internet of Vehicles (IoVs) under intelligent edge computing, brain-inspired computing techniques are proposed in this study, which is a promising biologically inspired method by using brain cognition mechanism for various applications. A neuromorphic approach in a scalable and fault-tolerant framework is presented, targeting to realize the navigation function for the edge computing in IoV applications. A novel fault-tolerant address event representation approach is proposed for the spike information routing, which makes the presented model both scalable and fault-tolerant. Experimental results reveal that the proposed approaches can enhance the communication distance, the load balancing and the maximum throughput of the neuromorphic system accordingly. Based on the proposed neuromorphic model, the effects of the dopamine level are investigated. Besides, the results show that the proposed work can realize the accurate obstacle avoidance for the edge IoV computing, and the performance of the proposed network is superior to the network without the proposed scalable and fault-tolerant design. Therefore, the proposed IoV model provides an experimental basis for the improvement of the IoV system.

Topik & Kata Kunci

Penulis (4)

S

Shuangming Yang

J

Jiangtong Tan

T

Tao Lei

B

B. Linares‐Barranco

Format Sitasi

Yang, S., Tan, J., Lei, T., Linares‐Barranco, B. (2023). Smart Traffic Navigation System for Fault-Tolerant Edge Computing of Internet of Vehicle in Intelligent Transportation Gateway. https://doi.org/10.1109/TITS.2022.3232231

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Informasi Jurnal
Tahun Terbit
2023
Bahasa
en
Total Sitasi
76×
Sumber Database
Semantic Scholar
DOI
10.1109/TITS.2022.3232231
Akses
Open Access ✓