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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Abstract	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.
AbstractList	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.
Author	Lei, Tao Linares-Barranco, Bernabe Yang, Shuangming Tan, Jiangtong
Author_xml	– sequence: 1 givenname: Shuangming orcidid: 0000-0002-8044-0860 surname: Yang fullname: Yang, Shuangming organization: School of Electrical and Information Engineering, Tianjin University, Tianjin, China – sequence: 2 givenname: Jiangtong surname: Tan fullname: Tan, Jiangtong organization: School of Electrical and Information Engineering, Tianjin University, Tianjin, China – sequence: 3 givenname: Tao orcidid: 0000-0002-2104-9298 surname: Lei fullname: Lei, Tao organization: School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi'an, China – sequence: 4 givenname: Bernabe surname: Linares-Barranco fullname: Linares-Barranco, Bernabe organization: Microelectronics Institute of Seville, Seville, Spain
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SubjectTerms	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
Title	Smart Traffic Navigation System for Fault-Tolerant Edge Computing of Internet of Vehicle in Intelligent Transportation Gateway
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