增强具有自我修复功能的视觉物联网mashup

João Pedro Dias, André Restivo, H. Ferreira
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引用次数: 3

摘要

物联网(IoT)系统已经扩展到不同的应用领域,从家庭自动化到工业制造过程。竞争厂商为了满足物联网解决方案的市场需求而匆忙开发,缺乏互操作性标准,以及总体上缺乏一套明确的最佳实践,导致了一个高度复杂、异构和脆弱的生态系统。一些工作正在推动可视化编程解决方案,以抽象潜在的复杂性并帮助人类对其进行推理。随着这些解决方案开始被广泛采用,它们的构建模块通常不会考虑可靠性问题。作为最流行的工具之一,Node-RED也缺乏这样的机制,无论是内置的还是通过扩展的。在这项工作中,我们提出了SHEN (Node-RED的自修复扩展),它提供了17个节点,这些节点共同支持在这个可视化框架内实现自修复策略。通过实际设备和故障注入技术验证了该方法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Empowering Visual Internet-of-Things Mashups with Self-Healing Capabilities
Internet-of-Things (IoT) systems have spread among different application domains, from home automation to industrial manufacturing processes. The rushed development by competing vendors to meet the market demand of IoT solutions, the lack of interoperability standards, and the overall lack of a defined set of best practices have resulted in a highly complex, heterogeneous, and frangible ecosystem. Several works have been pushing towards visual programming solutions to abstract the underlying complexity and help humans reason about it. As these solutions begin to meet widespread adoption, their building blocks usually do not consider reliability issues. Node-RED, being one of the most popular tools, also lacks such mechanisms, either built-in or via extensions. In this work we present SHEN (Self-Healing Extensions for Node-RED) which provides 17 nodes that collectively enable the implementation of self-healing strategies within this visual framework. We proceed to demonstrate the feasibility and effectiveness of the approach using real devices and fault injection techniques.
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