Empowering Visual Internet-of-Things Mashups with Self-Healing Capabilities

• Type: Article in International Conference Proceedings Book
• Date: 2021

Authors

João Pedro Dias (Author) FEUP; André Restivo (Author) FEUP; Hugo Sereno Ferreira (Author) FEUP

Conference proceedings International

Title: 3rd IEEE/ACM International Workshop on Software Engineering Research and Practices for the IoT SERP4IoT 2021, Madrid, Spain, June 3, 2021

Pages: 44-51

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 6 Citations

Other information

Authenticus ID: P-00T-MYE

DOI: 10.1109/serp4iot52556.2021.00014

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8