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Wireless Sensor Networks Technology and Its Application in Distributed Intelligent...
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Wireless Sensor Networks Technology and Its Application in Distributed Intelligent System

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 5203

Special Issue Editor

Dr. M. Mustafa Rafique

E-Mail Website
Guest Editor
Department of Computer Science, Rochester Institute of Technology, Rochester, NY 14623, USA
Interests: distributed and parallel systems; high-performance computing (HPC); system architecture and resource disaggregation; cloud computing; Internet of Things (IoT); edge computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue invites you to submit a paper that focuses on new approaches in the area of“Wireless Sensor Network Technology and Its Application in Distributed Intelligent Systems”.

In the era of Artificial Intelligence (AI) and the Internet of things (IoT), wireless sensor networks (WSNs) are essential for improving the quality of life. WSNs generate, collect and exchange huge amounts of data for offering a new paradigm of superior services identified by being available everywhere, at any time, and to anyone. Rapid developments in communication, software, and hardware technologies have facilitated wireless sensors, actuators, and heterogeneous devices connected via wireless communication channels. Nevertheless, WSN systems can act only as ordinary information systems based on predefined rules without distributed intelligence. By contrast, adding AI capabilities to WSNs would  allow services to be provided according to users’ contexts and in real time. Combining AI with WSNs opens new horizons and unlimited technological potential.

The distributed, intelligent processing of data and the building of distributed intelligent systems that can execute autonomous decisions are keys to developing smart WSN applications and services. Complex distributed intelligent systems (DIS) have been widely used for information processing in modern society due to the rapid development of AI applications and the need for intelligent information processing solutions. The advancement in modern communication and computing technologies enables the new application of DIS over WSNs. DIS has applications in various areas, such as smart cities, mobile sensor networks, autonomous vehicles, digital twins, robotics, and intelligent transportation systems. However, for the design and implementation of DIS, there are challenges related to data collection, communication, and information processing due to resource constraints on wireless devices and unreliable communication channels. Therefore, it is important to understand these constraints and limits in order to deploy modern applications of DIS, as well as to evaluate DIS.

Both analytical and experimental investigations are important to research on“Wireless Sensor Network Technology and Its Application in Distributed Intelligent Systems”.This Special Issue aims to present a research venue to publish new development and scientific innovations for realizing complex DIS. Both theory-focused and application-driven studies are invited, particularly with good technical merit on wireless sensor networks and distributed intelligent systems.

Dr. M. Mustafa Rafique
Guest Editor

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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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

  • Machine learning and deep learning methods for distributed sensor networks
  • Intelligent control and management in distributed sensor networks
  • Intelligent remote-control systems
  • Intelligent multi-agent systems
  • Intelligent sensor networks based on edge/fog/cloud computing
  • Distributed network intelligence
  • Swarm robotics
  • Smart spaces
  • Custom WSN routing and communication protocols for distributed intelligent systems

Published Papers (2 papers)

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Research

20 pages, 1086 KiB  
Article
An Efficient Distributed Approach for Cooperative Spectrum Sensing in Varying Interests Cognitive Radio Networks
by Maria Trigka and Elias Dritsas
Sensors 2022, 22(17), 6692; https://0-doi-org.brum.beds.ac.uk/10.3390/s22176692 - 04 Sep 2022
Cited by 3 | Viewed by 1515
Abstract
The rapid growth in wireless communications, coupled with insufficient utilization of the spectrum, led to the development of new wireless services and the promising technology of cognitive radio (CR) networks, which facilitate periodic access to the unoccupied spectrum bands and thus increases spectral [...] Read more.
The rapid growth in wireless communications, coupled with insufficient utilization of the spectrum, led to the development of new wireless services and the promising technology of cognitive radio (CR) networks, which facilitate periodic access to the unoccupied spectrum bands and thus increases spectral efficiency. A fundamental task in CR networks is spectrum sensing, through which unauthorized secondary users (SUs) detect unoccupied bands in the spectrum. To achieve this, an accurate estimate of the power spectrum is necessary. From this perspective, and given that many other factors can affect individual detection, such as pathloss and receiver uncertainty, we aim to improve its estimate by exploiting the spatial diversity in the SUs’ observations. Spectrum sensing is treated as a parameters estimation problem, assuming that the parameters’ vector of each SU consists of some global and partially common parameters. To exploit this modeling, distributed and cooperative spectrum sensing is the subject of interest in this study. Diffusion techniques, and especially the Adapt-Then-Combine (ATC) method will be exploited, where each SU cooperates with a group of nodes in its neighborhood that share the same parameters of interest. We consider a network of three static PUs with overlapping power spectrums, and thus, frequency bands. The performance of the employed method will be evaluated under two scenarios: (i) when the PUs spectrum varies, since some frequency bands are not yet utilized, and (ii) when the frequency bands of the PUs are fixed, but there is a mobile SU in the network, changing regions and parameters of interest. Experimental results and performance analysis reveal the ATC algorithm robustness and efficiency. Full article
(This article belongs to the Special Issue Wireless Sensor Networks Technology and Its Application in Distributed Intelligent System)
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19 pages, 4975 KiB  
Article
DeviceTalk: A No-Code Low-Code IoT Device Code Generation
by Whai-En Chen, Yi-Bing Lin, Tai-Hsiang Yen, Syuan-Ru Peng and Yun-Wei Lin
Sensors 2022, 22(13), 4942; https://0-doi-org.brum.beds.ac.uk/10.3390/s22134942 - 30 Jun 2022
Cited by 4 | Viewed by 2984
Abstract
The deployment of a client–server-based distributed intelligent system involves application development in both the network domain and the device domain. In the network domain, an application server (typically in the cloud) is deployed to execute the network applications. In the device domain, several [...] Read more.
The deployment of a client–server-based distributed intelligent system involves application development in both the network domain and the device domain. In the network domain, an application server (typically in the cloud) is deployed to execute the network applications. In the device domain, several Internet of Things (IoT) devices may be configured as, for example, wireless sensor networks (WSNs), and interact with each other through the application server. Developing the network and the device applications are tedious tasks that are the major costs for building a distributed intelligent system. To resolve this issue, a low-code or no-code (LCNC) approach has been purposed to automate code generation. As traditional LCNC solutions are highly generic, they tend to generate excess code and instructions, which will lack efficiency in terms of storage and processing. Fortunately, optimization of automated code generation can be achieved for IoT by taking advantage of the IoT characteristics. An IoT-based distributed intelligent system consists of the device domain (IoT devices) and the network domain (IoT server). The software of an IoT device in the device domain consists of the Device Application (DA) and the Sensor Application (SA). Most IoT LCNC approaches provide code generation in the network domain. Very few approaches automatically generate the DA code. To our knowledge, no approach supports the SA code generation. In this paper, we propose DeviceTalk, an LCNC environment for the DA and the SA code development. DeviceTalk automatically generates the code for IoT devices to speed up the software development in the device domain for a distributed intelligent system. We propose the DeviceTalk architecture, design and implementation of the code generation mechanism for the IoT devices. Then, we show how a developer can use the DeviceTalk Graphical User Interface (GUI) to exercise LCNC development of the device software. Full article
(This article belongs to the Special Issue Wireless Sensor Networks Technology and Its Application in Distributed Intelligent System)
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