The development of industrial Internet of Things (IIoT), big data, and artificial intelligence technologies is leading to a major change in the production system. The change is being propagated into the wave of transforming the existing system with a vertical structure into the corresponding horizontal platform or middleware. Accordingly, the way of acquiring IIoT data from an individual system is being altered to the way of being increasingly centralized through an integrated middleware of a scalable server or through a large platform. That said, middleware-based IIoT data acquisition must consider multiple factors, such as infrastructure (e.g., operation environment and network), protocol heterogeneity, interoperability (e.g., links with legacy systems), real-time, and security. This manuscript explains these five aspects in detail and provides a taxonomy of eighteen state-of-the-art IIoT data-acquisition middleware systems based on these aspects. To validate one of these aspects (network), we present our evaluation results at a real production site where IIoT data-acquisition loss rates are compared between wireless (long-term evolution) and wired networks. As a result, the wired communication can be more suitable for centralized IIoT data-acquisition middleware than wireless networks. Finally, we discuss several challenges in establishing the best IIoT data-acquisition middleware in a centralized way.

中文翻译：

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建立集中式数据获取中间件的工业物联网平台的调查：分类，实验和挑战

工业物联网（IIoT），大数据和人工智能技术的发展正在导致生产系统的重大变化。这种变化正在传播到将具有垂直结构的现有系统转换为相应的水平平台或中间件的浪潮中。因此，从单个系统获取IIoT数据的方式已更改为通过可伸缩服务器的集成中间件或大型平台日益集中化的方式。也就是说，基于中间件的IIoT数据获取必须考虑多个因素，例如基础架构（例如，操作环境和网络），协议异构性，互操作性（例如，与旧系统的链接），实时，和安全性。该手稿详细说明了这五个方面，并基于这些方面提供了十八种最新的IIoT数据采集中间件系统的分类法。为了验证这些方面（网络）之一，我们在真实的生产现场展示了评估结果，在现场比较了无线（长期演进）和有线网络之间的IIoT数据获取丢失率。因此，与无线网络相比，有线通信可能更适合于集中式IIoT数据获取中间件。最后，我们讨论了以集中方式建立最佳IIoT数据采集中间件的几个挑战。