车辆到一切的边缘计算:简短的回顾
Mohd Fikri Azli Abdullah1, Sumendra Yogarayan1, Siti Fatimah Abdul Razak1
1Faculty of Information Science and Technology, Multimedia University, Ayer Keroh, Melaka, 75450, Malaysia.
F1000Research
|April 10, 2024
概括
边缘计算 (EC) 可以通过处理更接近源头的数据来增强车辆到一切 (V2X) 通信,解决智能运输系统中的延迟和交付挑战. 本综述探讨了关于V2X适用性的EC方法.
科学领域:
- 智能运输系统 智能运输系统
- 无线通信无线通信
- 分布式计算 (Distributed Computing) 是一种分布式计算.
背景情况:
- 车辆与一切 (V2X) 通信对于未来的智能交通系统至关重要,它使车辆,基础设施,行人和网络之间的互动成为可能.
- V2X产生了巨大的数据量,需要低延迟和高吞吐量,这给处理和分发带来了重大挑战.
- 现有的研究缺乏对边缘计算 (EC) 适用于V2X服务的全面分析.
研究的目的:
- 探索和评估各种边缘计算 (EC) 方法在V2X通信和服务中的相关性和有效性.
- 识别和比较在V2X环境中实施EC的不同方法.
- 为了满足V2X的性能要求,例如动态交付和低延迟通信.
主要方法:
- 对现有适用于V2X通信的边缘计算 (EC) 方法的文献综述.
- 单独描述和对EC实施方法的比较分析.
- 专注于用于V2X数据处理的移动边缘计算,云端和雾计算等方法.
主要成果:
- 大多数经过审查的EC方法在预定义的场景下显示V2X的模拟适用性.
- 模拟显示了EC管理更接近数据源的V2X数据处理的潜力.
- 发现的一个局限性是,在带宽优化模拟中,可能会忽视关键数据.
结论:
- 边缘计算 (EC) 为解决V2X通信中的延迟和数据处理挑战提供了一个可行的解决方案.
- 需要进一步的研究来克服模拟的局限性,并充分描述EC在V2X中的作用.
- 这一综述为研究人员提供了更好地理解和实施EC for V2X服务的基础.
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