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.
翻译:开发日益复杂的IoT系统需要大型的工程环境,这些环境通常由不同供应商的工具组成,不一定相互融合。为了实现各种分析自动化,必须在工程活动的同时对多种工具的资源进行查询。在本文件中,我们确定这种查询能力的必要要求,并根据这些要求评价不同的结构。我们建议改进生命周期查询结构,以现有的跟踪资源系统协议为基础,并以MQT信息协议作为补充,以便实时更新仓库中的数据。作为侧重于开发IoT自动仓库的案例研究的一部分,我们采用了这一结构,将使用RESTful微观服务和相关数据的综合工具链。