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Journal ArticleDOI

Edge Computing in Industrial Internet of Things: Architecture, Advances and Challenges

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TLDR
Some typical application scenarios of edge computing in IIoT, such as prognostics and health management, smart grids, manufacturing coordination, intelligent connected vehicles (ICV), and smart logistics, are introduced.
Abstract
The Industrial Internet of Things (IIoT) is a crucial research field spawned by the Internet of Things (IoT). IIoT links all types of industrial equipment through the network; establishes data acquisition, exchange, and analysis systems; and optimizes processes and services, so as to reduce cost and enhance productivity. The introduction of edge computing in IIoT can significantly reduce the decision-making latency, save bandwidth resources, and to some extent, protect privacy. This paper outlines the research progress concerning edge computing in IIoT. First, the concepts of IIoT and edge computing are discussed, and subsequently, the research progress of edge computing is discussed and summarized in detail. Next, the future architecture from the perspective of edge computing in IIoT is proposed, and its technical progress in routing, task scheduling, data storage and analytics, security, and standardization is analyzed. Furthermore, we discuss the opportunities and challenges of edge computing in IIoT in terms of 5G-based edge communication, load balancing and data offloading, edge intelligence, as well as data sharing security. Finally, we introduce some typical application scenarios of edge computing in IIoT, such as prognostics and health management (PHM), smart grids, manufacturing coordination, intelligent connected vehicles (ICV), and smart logistics.

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Citations
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Journal ArticleDOI

Federated Learning for Internet of Things: A Comprehensive Survey

TL;DR: In this paper, a comprehensive survey of the emerging applications of federated learning in IoT networks is provided, which explores and analyzes the potential of FL for enabling a wide range of IoT services, including IoT data sharing, data offloading and caching, attack detection, localization, mobile crowdsensing and IoT privacy and security.
Journal ArticleDOI

Enabling Massive IoT Toward 6G: A Comprehensive Survey

TL;DR: A use case of fully autonomous driving is presented to show 6G supports massive IoT and some breakthrough technologies, such as machine learning and blockchain, in 6G are introduced, where the motivations, applications, and open issues of these technologies for massive IoT are summarized.
Journal ArticleDOI

Federated Learning for Internet of Things: A Comprehensive Survey

TL;DR: In this paper, a comprehensive survey of the emerging applications of federated learning in IoT networks is provided, which explores and analyzes the potential of FL for enabling a wide range of IoT services, including IoT data sharing, data offloading and caching, attack detection, localization, mobile crowdsensing and IoT privacy and security.
Journal ArticleDOI

Survey on Network Slicing for Internet of Things Realization in 5G Networks

TL;DR: This survey presents a comprehensive analysis of the exploitation of network slicing in IoT realisation and discusses the role of other emerging technologies and concepts, such as blockchain and Artificial Intelligence/Machine Learning (AI/ML) in network slicing and IoT integration.
Journal ArticleDOI

A Survey on Security and Privacy Issues in Edge-Computing-Assisted Internet of Things

TL;DR: In this paper, a comprehensive survey on security and privacy issues in the context of EC-assisted IoT is presented, including definitions, applications, architecture, advantages, and challenges, as well as several open challenges and future research directions for secure EC assisted IoT paradigm are also extensively provided.
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