Design of a Demonstration System for Vehicular Edge Computing Scheduling

With the widespread adoption of intelligent in-vehicle devices, demands for server computing performance and network transmission speed have significantly increased, while resources in vehicle-edge computing remain limited. This paper presents a demonstration and learning platform for vehicular edge...

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Bibliographic Details
Published inIEEE International Symposium on IT in Medicine and Education pp. 86 - 89
Main Authors Sun, Ye, Wu, Shuangnan, Shen, Li, Yan, Hao, Sheng, Feng
Format Conference Proceeding
LanguageEnglish
Published IEEE 13.09.2024
Subjects
Artificial intelligence
Autonomous vehicles
Deep learning
Dynamic scheduling
Edge computing
Heuristic algorithms
In-Vehicle Edge Computing
Processor scheduling
Resource management
Sensors
Task Scheduling
Vehicle dynamics
Web3D
Online AccessGet full text
ISSN2474-3828
DOI10.1109/ITME63426.2024.00027

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Summary:With the widespread adoption of intelligent in-vehicle devices, demands for server computing performance and network transmission speed have significantly increased, while resources in vehicle-edge computing remain limited. This paper presents a demonstration and learning platform for vehicular edge computing scheduling, employing Web3D technology to create a three-tier model of the architecture, vividly illustrating the resource allocation process. Addressing the dynamic complexity of in-vehicle network environments, this study abandons conventional scheduling methods, opting instead for deep learning algorithms to determine data offloading strategies that can adapt to changing conditions. Furthermore, the design incorporates a virtual academy where users can learn about edge computing, deep learning, and related subjects to gain a comprehensive understanding of the demo system.
ISSN:2474-3828
DOI:10.1109/ITME63426.2024.00027