Xu Hansong, Yu Wei, Griffith David, Golmie Nada
Towson University, MD, USA.
National Institute of Standards and Technology.
IEEE Access. 2018;6. doi: 10.1109/access.2018.2884906.
The vision of Industry 4.0, otherwise known as the fourth industrial revolution, is the integration of massively deployed smart computing and network technologies in industrial production and manufacturing settings for the purposes of automation, reliability, and control, implicating the development of an Industrial Internet of Things (I-IoT). Specifically, I-IoT is devoted to adopting the Internet of Things (IoT) to enable the interconnection of anything, anywhere, and at anytime in the manufacturing system context to improve the productivity, efficiency, safety and intelligence. As an emerging technology, I-IoT has distinct properties and requirements that distinguish it from consumer IoT, including the unique types of smart devices incorporated, network technologies and quality of service requirements, and strict needs of command and control. To more clearly understand the complexities of I-IoT and its distinct needs, and to present a unified assessment of the technology from a systems perspective, in this paper we comprehensively survey the body of existing research on I-IoT. Particularly, we first present the I-IoT architecture, I-IoT applications (i.e., factory automation (FA) and process automation (PA)) and their characteristics. We then consider existing research efforts from the three key systems aspects of control, networking and computing. Regarding control, we first categorize industrial control systems and then present recent and relevant research efforts. Next, considering networking, we propose a three-dimensional framework to explore the existing research space, and investigate the adoption of some representative networking technologies, including 5G, machine-to-machine (M2M) communication, and software defined networking (SDN). Similarly, concerning computing, we again propose a second three-dimensional framework that explores the problem space of computing in I-IoT, and investigate the cloud, edge, and hybrid cloud and edge computing platforms. Finally, we outline particular challenges and future research needs in control, networking, and computing systems, as well as for the adoption of machine learning, in an I-IoT context.
工业4.0，也就是第四次工业革命，其愿景是在工业生产和制造环境中大规模部署智能计算和网络技术，以实现自动化、可靠性和控制，这意味着工业物联网（I-IoT）的发展。具体而言，工业物联网致力于采用物联网（IoT），以实现制造系统环境中任何事物在任何地点、任何时间的互联，从而提高生产力、效率、安全性和智能化水平。作为一项新兴技术，工业物联网具有与消费物联网不同的独特属性和要求，包括所包含的智能设备的独特类型、网络技术和服务质量要求，以及严格的命令和控制需求。为了更清楚地理解工业物联网的复杂性及其独特需求，并从系统角度对该技术进行统一评估，在本文中，我们全面调研了现有的关于工业物联网的研究。特别是，我们首先介绍了工业物联网架构、工业物联网应用（即工厂自动化（FA）和过程自动化（PA））及其特点。然后，我们从控制、网络和计算这三个关键系统方面考虑现有的研究工作。关于控制，我们首先对工业控制系统进行分类，然后介绍近期的相关研究工作。接下来，考虑网络方面，我们提出一个三维框架来探索现有的研究空间，并研究一些代表性网络技术的采用情况，包括5G、机器对机器（M2M）通信和软件定义网络（SDN）。同样，关于计算，我们再次提出一个三维框架，该框架探索工业物联网中计算的问题空间，并研究云、边缘以及混合云和边缘计算平台。最后，我们概述了工业物联网环境下控制、网络和计算系统以及机器学习采用方面的特定挑战和未来研究需求。
