Improving lifecycle query in integrated toolchains using linked data and MQTT-based data warehousing
This addresses integration challenges in IoT toolchains for engineers, but it is incremental as it builds on existing protocols.
The paper tackled the problem of executing queries across multiple tools in complex IoT engineering environments by proposing an improved lifecycle query architecture that integrates the TRS protocol with MQTT for real-time data updates, implemented in a case study for an IoT automated warehouse.
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.