在雾计算中基于机器学习的资源管理:系统的文献综述
Fahim Ullah Khan1, Ibrar Ali Shah1, Sadaqat Jan1
1Department of Computer Software Engineering, University of Engineering and Technology, Mardan 23200, Pakistan.
Sensors (Basel, Switzerland)
|February 13, 2025
概括
深度学习 (DL) 在雾计算中主导了资源管理,超过了传统的机器学习 (ML) 技术. 这次审查强调了DL的重点.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 分布式计算 (Distributed Computing) 是一种分布式计算.
背景情况:
- 雾计算环境需要高效的资源管理.
- 机器学习 (ML) 和深度学习 (DL) 提供了潜在的解决方案.
- 优化资源配置对于雾计算性能至关重要.
研究的目的:
- 系统地审查基于ML的技术,用于雾计算中的资源管理.
- 确定流行的ML/DL方法及其应用.
- 分析文献中涉及的关键因素和挑战.
主要方法:
- 按照PRISMA协议进行的系统文献审查.
- 分析68篇关于ML/DL用于雾计算资源管理的扩展研究论文.
- 基于所涉及的因素和挑战对技术进行分类.
主要成果:
- 深度学习 (DL) 技术是首选的,在66%的审查研究中使用,相比之下,ML的34%.
- 延迟 (77%),能源消耗 (44%) 和QoS (33%) 是最常见的因素.
- 计算资源,延迟,可扩展性,数据质量和模型可解释性是各种ML/DL方法所应对的关键挑战.
结论:
- 在雾计算中,DL显示了资源管理的强趋势.
- 解决延迟,能源和QoS对于优化至关重要.
- ML/DL技术有效地应对雾计算资源管理中的各种挑战.
相关概念视频
02:12Short-distance Transport of Resources
Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
01:21Distributed Loads: Problem Solving
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...