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Industrial Wireless Networks: Algorithms, Protocols and Applications
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Industrial Wireless Networks: Algorithms, Protocols and Applications

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information and Communications Technology".

Deadline for manuscript submissions: closed (15 February 2021) | Viewed by 9416

Special Issue Editors

Prof. Dr. Federico Tramarin

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Guest Editor
Department of Management and Engineering, University of Padova | UNIPD, Padova, Italy
Interests: Industrial wireless networks; Time sensitive networks; industrial communications; real-time systems; distributed measurement systems; networked embedded systems; Industrial Internet of Thing
Special Issues, Collections and Topics in MDPI journals
Dr. Luca Leonardi

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Guest Editor
Department of Electrical, Electronic and Computer Engineering, University of Catania—UNICT, Catania, Italy
Interests: real-time industrial networks; low power wide area networks; wireless sensor and actuator networks; industrial internet of things; automotive communications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, the industrial scene has witnessed the rise of interest in the Industry 4.0 revolution. This has triggered even further information and communication technology (ICT) pervasiveness within the industrial realm, with wireless networks playing a disruptive role in many areas to accomplish one of the most important transformations of the last few decades.

One of the key enablers driving this ongoing industry digitalization process can be recognized in the industrial Internet of Things (IIoT) paradigm, where the potentialities of IoT are extended to industrial wireless communications in order to facilitate time-, safety- and mission-critical applications with unprecedented integration among heterogeneous systems, enhanced interoperability, and availability.

The evolution of industrial wireless communications (IWC) requires novel solutions and protocols able to satisfy both the new aforementioned challenges and the requirements of high reliability, robustness, availability, and timeliness in the information exchange between devices, with the growing need for low-power consumption to exploit energy-limited devices.

In light of this, several existing wireless technologies, primarily aimed at different application fields, may represent promising candidates for boosting prospective industrial networks and services. Furthermore, emerging paradigms are pointing attention to ultra-reliable and ultra-low latency communications as well as to time-sensitive networks, with the rise of interest in TSN over wireless and 5G technologies. These can be profitably leveraged in a broad range of industrial-level applications, such as smart factories, transportation systems, energy grids, and similar application scenarios.

This Special Issue on industrial wireless communication is targeted at industrial and academic researchers addressing subjects relevant to industrial wireless networks. Topics of interest include, but are not limited to, the following:

  • Industrial Internet of Things;
  • Protocols for IWC and IWSN;
  • Real-time industrial wireless communications;
  • Edge and fog computing for IWSN;
  • Modeling of architectures and communication systems;
  • Scheduling algorithms;
  • Software-defined networking (SDN) and network slicing for IWC;
  • IWC testbeds and applications;
  • Performance evaluation of standard wireless communication protocols for industrial applications;
  • Medium access control protocols for IWC;
  • Low-power wide area networks;
  • New technologies for low-power wireless sensor networks in Industry 4.0;
  • Security and safety solutions for ICPS;
  • High-performance industrial wireless communications;
  • 5G and 6G networks for critical control systems.

Prof. Dr. Federico Tramarin
Dr. Luca Leonardi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Real-time wireless communications
  • Industrial Internet of Thing
  • Industrial Wireless Sensor Networks
  • Low power wireless technologies
  • Low Power Wide Area Networks

Published Papers (2 papers)

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Research

25 pages, 1482 KiB  
Article
Combining Network Coding and Retransmission Techniques to Improve the Communication Reliability of Wireless Sensor Network
by Suelen Laurindo, Ricardo Moraes, Carlos Montez and Francisco Vasques
Information 2021, 12(5), 184; https://doi.org/10.3390/info12050184 - 24 Apr 2021
Cited by 12 | Viewed by 3042
Abstract
This paper addresses the use of network coding algorithms combined with adequate retransmission techniques to improve the communication reliability of Wireless Sensor Networks (WSN). Basically, we assess the recently proposed Optimized Relay Selection Technique (ORST) operating together with four different retransmission techniques, three [...] Read more.
This paper addresses the use of network coding algorithms combined with adequate retransmission techniques to improve the communication reliability of Wireless Sensor Networks (WSN). Basically, we assess the recently proposed Optimized Relay Selection Technique (ORST) operating together with four different retransmission techniques, three of them applying network coding algorithms. The target of this assessment is to analyze the impact upon the communication reliability from each of the proposed retransmission techniques for WSN applications. In addition, this paper presents an extensive state-of-the-art study in what concerns the use of network coding techniques in the WSN context. The initial assumption of this research work was that the ORST operating together network coding would improve the communication reliability of WNS. However, the simulation assessment highlighted that, when using the ORST technique, retransmission without network coding is the better solution. Full article
(This article belongs to the Special Issue Industrial Wireless Networks: Algorithms, Protocols and Applications)
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12 pages, 1367 KiB  
Article
Multi-Sensor Data Fusion Algorithm for Indoor Fire Early Warning Based on BP Neural Network
by Lesong Wu, Lan Chen and Xiaoran Hao
Information 2021, 12(2), 59; https://doi.org/10.3390/info12020059 - 30 Jan 2021
Cited by 42 | Viewed by 5715
Abstract
Fire early warning is an important way to deal with the faster burning rate of modern home fires and ensure the safety of the residents’ lives and property. To improve real-time fire alarm performance, this paper proposes an indoor fire early warning algorithm [...] Read more.
Fire early warning is an important way to deal with the faster burning rate of modern home fires and ensure the safety of the residents’ lives and property. To improve real-time fire alarm performance, this paper proposes an indoor fire early warning algorithm based on a back propagation neural network. The early warning algorithm fuses the data of temperature, smoke concentration and carbon monoxide, which are collected by sensors, and outputs the probability of fire occurrence. In this study, non-uniform sampling and trend extraction were used to enhance the ability to distinguish fire signals and environmental interference. Data from six sets of standard test fire scenarios and six sets of no-fire scenarios were used to test the algorithm proposed in this paper. The test results show that the proposed algorithm can correctly alarm six standard test fires from these 12 scenarios, and the fire detection time is shortened by 32%. Full article
(This article belongs to the Special Issue Industrial Wireless Networks: Algorithms, Protocols and Applications)
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