车辆边缘计算网络中的边缘服务器的基于游戏的计算资源分配方案,考虑多种任务卸载模式
Xiangyan Liu1, Jianhong Zheng1, Meng Zhang2
1School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Sensors (Basel, Switzerland)
|January 11, 2024
概括
本研究介绍了车辆边缘计算网络 (VECN) 中的部分任务卸载,以改进车辆互联网 (IoV). 拟议的算法优化了多任务车辆 (TaV) 的资源分配和任务卸载比率,提高了服务质量 (QoS).
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 网络工程 网络工程
背景情况:
- 新兴的车辆应用程序增加了车辆互联网 (IoV) 的负担.
- 车辆边缘计算网络 (VECN) 通过实现部分任务卸载提供了一个解决方案.
- 优化任务卸载比率和边缘服务器 (ES) 资源配置对于VECN至关重要.
研究的目的:
- 提出一个新的算法,用于VECN中的多任务车辆 (TaV) 系统的计算资源分配.
- 共同优化服务车辆 (SeV) 选择,任务卸载策略和计算资源分配.
- 通过尽量减少处理延迟,确保TaVs的服务质量 (QoS).
主要方法:
- 提出了一个基于最佳响应的集中式多TaV计算资源分配算法 (BR-CMCRA).
- 服务车辆 (SeV) 根据候选SeV (CSV) 的通道收益进行选择.
- 准确的潜在游戏 (EPG) 框架用于逐步计算资源分配以最大化收益.
主要成果:
- BR-CMCRA算法有效地分配计算资源,并确定任务卸载比率.
- 拟议的算法在模拟中显示了与现有的基本算法相比更高的性能.
- 与任务处理延迟相关的实用功能确保了TaVs的增强的QoS.
结论:
- 在VECN中部分卸载任务是管理IoV负担的可行策略.
- 在TaV系统中,BR-CMCRA算法为资源分配和任务卸载提供了有效的解决方案.
- 开发的方法增强了QoS,并在VECN环境中优于传统方法.
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