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

TL;DR

This paper introduces SHEN, a set of 17 nodes for Node-RED that enable self-healing strategies in IoT visual programming, demonstrated through real devices and fault injection.

Contribution

It presents SHEN, the first comprehensive self-healing extension for Node-RED, enhancing IoT system reliability within visual programming environments.

Findings

SHEN effectively detects and repairs faults in IoT setups.

Real device experiments confirm improved system resilience.

Fault injection tests demonstrate robustness of self-healing strategies.

Abstract

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.