Fog/Edge/Cloud Computing in the Internet of Things

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 15 October 2024 | Viewed by 1435

Special Issue Editors


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Guest Editor
Computer Science, Faculty of Environment, Science and Economy, University of Exeter, Exeter EX4 4QJ, UK
Interests: distributed systems; resource optimisation; Internet of Things; machine learning

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Guest Editor
College of Computer and Cyber Security, Fujian Normal University, Fuzhou 350007, China
Interests: network security; blockchain; machine learning; IoT

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Guest Editor
Computer Science, Faculty of Environment, Science and Economy, University of Exeter, Exeter EX4 4QJ, UK
Interests: edge–cloud computing; federated learning; wireless networks; applied machine learning

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is driving a revolutionary transformation by introducing network connectivity into traditional devices, making objects from home appliances to industrial tools smart. This paradigm shift is empowered by various sensors with data collection, processing, and transmission capabilities, as well as powerful servers that provide computing and storage capabilities.

In recent years, fog/edge computing has been emerging as complementary computing paradigms that leverage computing and storage resources at the network edge to decrease the latency of artificial intelligence (AI) applications, protect data privacy, improve workload scheduling performance, etc. The combination of fog, edge, and cloud computing adds flexibility in the performance of computation or storage-intensive tasks (e.g., image/video recognition, content caching, anomaly detection). In IoT, users or service providers can choose to run different IoT application tasks at the edge for faster processing or upload them to the cloud infrastructures for more robust results based on specific requirements.

This Special Issue aims to address issues in the state-of-the-art fog/edge/cloud computing approaches and techniques applicable to the Internet of Things, providing cross-disciplinary ideas to address present and future challenges. Topics of interest include, but are not limited to, the following:

  • Fog/edge/cloud computing-based IoT frameworks and architectures design.

  • Distributed network communication protocols for fog/edge/cloud computing in IoT.

  • Fog/edge/cloud computing for IoT data processing, modelling, and analysis.

  • Workload scheduling in fog/edge/cloud computing-based IoT applications.

  • Privacy preserving for fog/edge/cloud computing in IoT.

  • Anomaly detection for fog/edge/cloud computing in IoT.

  • Hardware-assisted design for fog/edge/cloud computing in IoT.

  • Network traffic prediction and optimization for fog/edge/cloud computing in IoT.

Dr. Jia Hu
Prof. Dr. Hui Lin
Dr. Zi Wang
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • fog/edge/cloud computing
  • Internet of Things (IoT)
  • workload scheduling and optimization
  • network communication protocol
  • data processing, modelling, and analysis
  • anomaly detection
  • network traffic prediction and optimization
  • security and privacy in IoT

Published Papers (1 paper)

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Research

26 pages, 8035 KiB  
Article
System Architecture for Diagnostics and Supervision of Industrial Equipment and Processes in an IoE Device Environment
by Marek Bolanowski, Andrzej Paszkiewicz, Tomasz Żabiński, Grzegorz Piecuch, Mateusz Salach and Krzysztof Tomecki
Electronics 2023, 12(24), 4935; https://doi.org/10.3390/electronics12244935 - 08 Dec 2023
Cited by 1 | Viewed by 907
Abstract
IoE components are becoming an integral part of our lives and support the operation of systems such as smart homes, smart cities, or Industry 4.0. The large number and variety of IoE components force the creation of flexible systems for data acquisition, processing, [...] Read more.
IoE components are becoming an integral part of our lives and support the operation of systems such as smart homes, smart cities, or Industry 4.0. The large number and variety of IoE components force the creation of flexible systems for data acquisition, processing, and analysis. The work presents a proposal for a new flexible architecture model and technology stack designed for the diagnostics and monitoring of industrial components and processes in an IoE device environment. The proposed solutions allow creating custom flexible systems for managing a distributed IoT environment, including the implementation of innovative mechanisms like, for example: predictive maintenance, anomaly detection, business intelligence, optimization of energy consumption, or supervision of the manufacturing process. In the present study, two detailed system architectures are proposed, and one of them was implemented. The developed system was tested in near-production conditions using a real IoT device infrastructure including industrial systems, drones, and sensor networks. The results showed that the proposed model of a central data-acquisition and -processing system allows the flexible integration of various IoE solutions and has a very high implementation potential wherever there is a need to integrate data from different sources and systems. Full article
(This article belongs to the Special Issue Fog/Edge/Cloud Computing in the Internet of Things)
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