介绍了COGNIFOG框架:架构,构建块和通向认知连接的道路
Toni Adame1, Emna Amri2, Grigoris Antonopoulos3
1Fundació i2CAT, Gran Capità 2-4, 08034 Barcelona, Spain.
Sensors (Basel, Switzerland)
|August 29, 2024
概括
新的认知雾框架COGNIFOG使用人工智能进行自主物联网边缘云操作. 早期测试显示,网络资源使用得到改善,提高了计算环境中的效率和可靠性.
科学领域:
- 计算机科学 计算机科学
- 分布式计算 (Distributed Computing) 是一种分布式计算.
- 人工智能的人工智能
背景情况:
- 无处不在的计算需要实时处理,安全和能源效率.
- 雾计算使资源更接近数据源,但在异质环境中面临挑战.
- 资源分配,管理,安全和连接是雾计算中的关键问题.
研究的目的:
- 介绍COGNIFOG,一个新的认知雾框架.
- 在物联网-边缘-云连续性中实现自主运行,适应性和可扩展性.
- 在下一代计算环境中提高效率和可靠性.
主要方法:
- 利用智能,分散的决策流程.
- 利用机器学习算法和分布式计算原则.
- 整合自主管理的认知能力.
主要成果:
- 初步结果显示,网络资源利用率有望改善.
- 在现实世界物联网场景中使用以连接为重点的COGNIFOG块证明了提高效率.
- 显示了提高可靠性和无物理数字集成的潜力.
结论:
- COGNIFOG提供了一种有前途的方法来应对雾计算的挑战.
- 预计该框架的认知能力将提高效率和可靠性.
- 进一步的开发旨在增强智能,弹性和适应不断变化的计算需求的能力.
关键词:
这就是为什么物联网物联网物联网.物联网-边缘-云连续性连续性认知连接性的认知连接性提供机密计算服务.边缘计算是一种边缘计算.雾计算 雾计算 雾计算智能系统 智能系统是智能系统.服务编排服务编排.更多相关视频
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