A look into smart factory for Industrial IoT driven by SDN technology: A comprehensive survey of taxonomy, architectures, issues and future research orientations

IF 5.2 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Nteziriza Nkerabahizi Josbert, Min Wei, Ping Wang, Ahsan Rafiq
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引用次数: 0

Abstract

The Internet of Things (IoT) provides a major contribution to the innovation of smart manufacturing and industrial automation. Due to IoT, network devices and intelligent machines exchange information through different types of Internet connection and processes are predominantly automated. This reduces significantly the need for more human intervention and supports high performance. Nevertheless, the utilization of IoT in industrial automation called Industrial IoT (IIoT) has several issues, including the management of applications and IIoT devices. Moreover, heterogeneous networks and tremendous devices deployed in the IIoT environment require flexible configuration and reconfiguration according to the change for ensuring dynamic performance. We argue that Software-Defined Networking (SDN) is one of the technologies that can be used to solve some of the previously mentioned issues. In this paper, we propose a survey for the implementation of SDN solutions in IIoT and discuss the pros and cons brought about by this synergy named “SDN-IIoT”. We explore the current articles on SDN-IIoT by considering different crucial domains such as flow installation techniques, fault tolerance, traffic routing optimization, resource management, energy efficiency, real-time, and network security. Furthermore, we analyze Artificial Intelligence (AI)/Machine Learning (ML) tasks to improve the performance of SDN-IIoT and the deployment of different technologies like Network Function Virtualization (NFV) and Time-Sensitive Networking (TSN) in SDN-IIoT. After observing the limitations of existing SDN-IIoT architectures, we propose an improved candidate architecture for SDN-IIoT based on a hierarchical distributed control plane. The new SDN-IIoT architecture contains AI, Industrial Backhaul Network (IBN), Dynamic Hash Table (DHT), AdaptFlow protocol, and edge/cloud storages. This paper selects the five most used SDN controllers by the literature review and identifies the features of each SDN controller. In the end, we provide open challenges and future research orientations in SDN-IIoT. We hope that this paper will be helpful for engineers, organizations, and researchers on the innovation of IIoT and SDN technologies.

研究由 SDN 技术驱动的工业物联网智能工厂:对分类、架构、问题和未来研究方向的全面调查
物联网(IoT)为智能制造和工业自动化的创新做出了重大贡献。由于物联网的存在,网络设备和智能机器通过不同类型的互联网连接交换信息,流程主要实现自动化。这大大减少了对更多人工干预的需求,并支持高性能。然而,物联网在工业自动化领域的应用被称为工业物联网(IIoT),它存在一些问题,包括应用程序和 IIoT 设备的管理。此外,部署在 IIoT 环境中的异构网络和巨大设备需要根据变化进行灵活配置和重新配置,以确保动态性能。我们认为,软件定义网络(SDN)是可以用来解决前面提到的一些问题的技术之一。在本文中,我们提出了在 IIoT 中实施 SDN 解决方案的调查,并讨论了这种名为 "SDN-IIoT "的协同作用所带来的利弊。我们通过考虑流量安装技术、容错、流量路由优化、资源管理、能效、实时性和网络安全等不同的关键领域,探讨了当前有关 SDN-IIoT 的文章。此外,我们还分析了提高 SDN-IIoT 性能的人工智能(AI)/机器学习(ML)任务,以及在 SDN-IIoT 中部署网络功能虚拟化(NFV)和时间敏感网络(TSN)等不同技术的情况。在观察了现有 SDN-IIoT 架构的局限性后,我们提出了一种基于分层分布式控制平面的 SDN-IIoT 改进候选架构。新的 SDN-IIoT 架构包含人工智能、工业回程网络(IBN)、动态哈希表(DHT)、AdaptFlow 协议和边缘/云存储。本文通过文献综述选出了五种最常用的 SDN 控制器,并指出了每种 SDN 控制器的特点。最后,我们提出了 SDN-IIoT 的开放挑战和未来研究方向。希望本文能对工程师、组织和研究人员在 IIoT 和 SDN 技术创新方面有所帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
10.50
自引率
8.70%
发文量
656
审稿时长
29 days
期刊介绍: In 2022 the Journal of King Saud University - Computer and Information Sciences will become an author paid open access journal. Authors who submit their manuscript after October 31st 2021 will be asked to pay an Article Processing Charge (APC) after acceptance of their paper to make their work immediately, permanently, and freely accessible to all. The Journal of King Saud University Computer and Information Sciences is a refereed, international journal that covers all aspects of both foundations of computer and its practical applications.
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