| 标题 |
 Q-Learning Based Computation Offloading with Minimizing the Cost in Vehicle Edge Computing 基于Q学习的车辆边缘计算成本最小化计算卸载
相关领域
计算卸载
计算机科学
边缘计算
计算
GSM演进的增强数据速率
人工智能
算法
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| 网址 | |
| DOI |
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| 其它 | The advancement of autonomous driving and vehicle networking technologies is continuously spawning new vehicle applications, improving traffic safety and the overall driving experience is a key goal. Yet, this is challenged by the limited computing and storage capacities available on-board. certain computation-heavy tasks miss their deadlines, necessitating the use of edge computing. Vehicle edge (VEC) serves as a potent solution for enhancing vehicular computing capabilities. This paper presents a model for task offloading in vehicular edge computing (VEC).Our approach leverages idle resources in vehicles to support edge computing offloading within a heterogeneous network. To reduce system expenses, |
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