Improving lifecycle query in integrated toolchains using linked data and MQTT-based data warehousing

TL;DR

This paper presents an enhanced lifecycle query architecture for complex IoT systems, integrating linked data, MQTT messaging, and TRS protocol to enable real-time data updates across diverse engineering tools.

Contribution

It introduces a novel architecture combining TRS, MQTT, and linked data to improve real-time query capabilities in IoT toolchains.

Findings

Architecture supports real-time data updates in IoT environments

Implementation demonstrates effective integration of multiple tools

Enhances automation and analysis in complex IoT systems

Abstract

The development of increasingly complex IoT systems requires large engineering environments. These environments generally consist of tools from different vendors and are not necessarily integrated well with each other. In order to automate various analyses, queries across resources from multiple tools have to be executed in parallel to the engineering activities. In this paper, we identify the necessary requirements on such a query capability and evaluate different architectures according to these requirements. We propose an improved lifecycle query architecture, which builds upon the existing Tracked Resource Set (TRS) protocol, and complements it with the MQTT messaging protocol in order to allow the data in the warehouse to be kept updated in real-time. As part of the case study focusing on the development of an IoT automated warehouse, this architecture was implemented for a toolchain integrated using RESTful microservices and linked data.