边缘数据处理的模块化框架:设计和实施
Lubomir Urblik1, Erik Kajati1, Peter Papcun1
1Department of Cybernetics and Artificial Intelligence, Faculty of EE & Informatics, Technical University of Kosice, 042 00 Kosice, Slovakia.
Sensors (Basel, Switzerland)
|September 9, 2023
概括
本研究介绍了一个容器化边缘计算框架,用于高效的物联网 (IoT) 数据处理. 它解决了云计算的局限性,为时间敏感的边缘分析提供了统一的模块化解决方案.
科学领域:
- 计算机科学 计算机科学
- 数据科学数据科学数据科学
- 网络工程 网络工程
背景情况:
- 物联网 (IoT) 设备的扩散产生了庞大的数据集,由于延迟,带宽和隐私问题,压倒了传统的云架构.
- 现有的边缘计算解决方案缺乏统一的方法,通常需要设备特定的应用程序或仅依赖容器化来部署和监控.
研究的目的:
- 提出和评估一个通用的,模块化的边缘计算框架,用于高效的数据处理和分析.
- 通过标准化,容器化的方法来解决边缘环境的异质性.
主要方法:
- 实施一个边缘计算框架,利用容器化实现可扩展的部署.
- 开发一个流式提取,转换,加载 (ETL) 管道,用于实时数据处理.
- 利用ZeroMQ作为有效数据传输的通信支柱.
主要成果:
- 拟议的框架有效地处理和分析网络边缘的数据.
- 容器化使得在各种边缘环境中实现可扩展和灵活的部署.
- 流式ETL管道证明了适用于时间敏感的物联网应用的适用性.
结论:
- 开发的边缘计算框架为物联网数据处理挑战提供了统一和模块化解决方案.
- 容器化是有效和可扩展的边缘分析的关键推动因素.
- 该框架非常适合时间敏感的应用程序,需要低延迟和高吞吐量.
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