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

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 a...

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Vydané v:IEEE transactions on intelligent transportation systems Ročník 24; číslo 11; s. 1 - 12
Hlavní autori: Yang, Shuangming, Tan, Jiangtong, Lei, Tao, Linares-Barranco, Bernabe
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.11.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Brain
brain-inspired
Cognition
Computational modeling
Dopamine
Edge computing
Fault tolerance
Fault tolerant systems
intelligent edge computing
Internet of Vehicles
Navigation
Navigation systems
neuromorphic
Neuromorphics
Obstacle avoidance
Real-time systems
ISSN:1524-9050, 1558-0016
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2022.3232231