LVUCB: an efficient vehicle network task scheduling system

With the development of vehicle edge computing technology, one of challenge is that in a high-speed motion, the vehicle leads to rapid and unpredictable changes in network topology, wireless channel status and available computing resources. Based on the vehicle edge computing technology, we applied...

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Vydané v:Multimedia tools and applications Ročník 84; číslo 29; s. 35409 - 35425
Hlavní autori: Lin, Qiang, Kuang, Haibo, Wang, Can, Guo, Yang, Zhang, Xilin, Luo, Jiawei
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.09.2025
Springer Nature B.V
Predmet:
1231: IoT-driven Computer Vision Technology for Smart Transportation Applications
Algorithms
Communication
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Decision making
Edge computing
Energy consumption
Gaming machines
Intelligent transportation systems
Multimedia Information Systems
Network topologies
Optimization
Quality of service
Scheduling
Special Purpose and Application-Based Systems
Task scheduling
Transportation networks
Vehicles
Vehicle Edge Computing
Simulation of Urban Mobility
Multi-armed Bandit
Intelligent Transportation System
ISSN:1573-7721, 1380-7501, 1573-7721
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Popis
Shrnutí:With the development of vehicle edge computing technology, one of challenge is that in a high-speed motion, the vehicle leads to rapid and unpredictable changes in network topology, wireless channel status and available computing resources. Based on the vehicle edge computing technology, we applied a vehicle network task scheduling framework, and proposed an algorithm, named LVUCB. In addition, we also designed and implemented a vehicle network task scheduling system based on this algorithm. Simulation experiments show that the proposed algorithm can decrease 15% delay than the classic UCB algorithm and meet mostly needs of vehicle network task management in intelligent transportation system.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1573-7721
1380-7501
1573-7721
DOI:10.1007/s11042-023-15311-2