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Wireless Sensor Networks: Signal Processing and Communications
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Wireless Sensor Networks: Signal Processing and Communications

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

Deadline for manuscript submissions: 20 June 2025 | Viewed by 6597

Special Issue Editor

Dr. Toni Adame Vázquez

E-Mail Website
Guest Editor
IoT Research Group, i2CAT Foundation, 08034 Barcelona, Spain
Interests: wireless sensor networks; IoT; MAC; UWB; Future Internet

Special Issue Information

Dear Colleagues,

Wireless sensor networks (WSNs) are considered one of the most important data sources of Internet of Things (IoT) applications. Consisting of tens, hundreds or even thousands of devices, WSNs can collect data on the ground and in real time from a wide range of physical and environmental variables. However, this massive data generation is pushing network capacity to its limits, and the need to support advanced processing at the periphery of the network instead of at the cloud, or elsewhere along the edge-to-cloud path, is becoming more and more relevant. Analyzing and managing data closer to where they are generated, rather than routing them to a data center, reduces network load, makes more efficient use of available energy and satisfies the requirements of ultra-low latency applications, such as from Industry 4.0 or autonomous vehicles. On the other hand, several new security and privacy challenges arise in edge/fog computing architectures, because of their higher vulnerability to device theft and/or manipulation, identity theft, and data eavesdropping. This Special Issue calls for high-quality, innovative, and original works that elaborate on the use of novel edge/fog computing architectures to support the effective use of WSNs in novel IoT applications.

Dr. Toni Adame Vázquez
Guest Editor

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. 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

  • edge/fog computing architectures and routing strategies for WSNs
  • cloud–edge continuum
  • resource allocation and orchestration of WSN devices in edge/fog computing
  • novel architectures and protocols for WSN communication
  • hybrid communication architectures for WSN: Terrestrial and Proposed
  • low-latency applications for the IoT (e.g., industrial automation and autonomous vehicles)
  • localization and tracking in WSNs
  • security issues of WSNs in edge/fog computing paradigms.

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Published Papers (5 papers)

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Research

25 pages, 10446 KiB  
Article
Designing an Adaptive Underwater Visible Light Communication System
by Sana Rehman, Yue Rong and Peng Chen
Sensors 2025, 25(6), 1801; https://doi.org/10.3390/s25061801 - 14 Mar 2025
Viewed by 480
Abstract
The Internet of Underwater Things (IoUT) has attracted significant attention from researchers due to the fact that seventy percent of the Earth’s surface is covered by water. Reliable underwater communication is the enabler of IoUT. Different carriers, such as electromagnetic waves, sound, and [...] Read more.
The Internet of Underwater Things (IoUT) has attracted significant attention from researchers due to the fact that seventy percent of the Earth’s surface is covered by water. Reliable underwater communication is the enabler of IoUT. Different carriers, such as electromagnetic waves, sound, and light, are used to transmit data through the water. Among these, optical waves are considered promising due to their high data rates and relatively good bandwidth efficiency, as water becomes transparent to light in the visible spectrum (400–700 nm). However, limitations such as link range, path loss, and turbulence lead to low power and, consequently, a low signal-to-noise ratio (SNR) at the receiver. In this article, we present the design of a smart transceiver for bidirectional communication. The system adapts the divergence angle of the optical beam from the transmitter based on the power of the signal received. This paper details the real-time data transmission process, where the transmitting station consists of a light fidelity (Li-Fi) transmitter with a 470 nm blue-light-emitting diode (LED) and a software-defined radio (SDR) for underwater optical communication. The receiving station is equipped with a Li-Fi receiver, which includes a photodetector with a wide field of view and an SDR. Furthermore, we use pulse position modulation (PPM), which demonstrates promising results for real-time transmission. A key innovation of this paper is the integration of the Li-Fi system with the SDR, while the system adapts dynamically using a servo motor and an Arduino microcontroller assembly. The experimental results show that this approach not only increases throughput but also enhances the robustness and efficiency of the system. Full article
(This article belongs to the Special Issue Wireless Sensor Networks: Signal Processing and Communications)
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25 pages, 5891 KiB  
Article
Discrete Event System Specification for IoT Applications
by Iman Alavi Fazel and Gabriel Wainer
Sensors 2024, 24(23), 7784; https://doi.org/10.3390/s24237784 - 5 Dec 2024
Viewed by 874
Abstract
The Internet of Things (IoT) has emerged as a transformative technology with a variety of applications across various industries. However, the development of IoT systems is hindered by challenges such as interoperability, system complexity, and the need for streamlined development and maintenance processes. [...] Read more.
The Internet of Things (IoT) has emerged as a transformative technology with a variety of applications across various industries. However, the development of IoT systems is hindered by challenges such as interoperability, system complexity, and the need for streamlined development and maintenance processes. In this study, we introduce a robust architecture grounded in discrete event system specification (DEVS) as a model-driven development solution to overcome these obstacles. Our proposed architecture utilizes the publish/subscribe paradigm, and it also adds to the robustness of the proposed solution with the incorporation of the Brooks–Iyengar algorithm to enhance fault tolerance against unreliable sensor readings. We detail the DEVS specification that is used to define this architecture and validate its effectiveness through a detailed home automation case study that integrates multiple sensors and actuators. Full article
(This article belongs to the Special Issue Wireless Sensor Networks: Signal Processing and Communications)
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28 pages, 1442 KiB  
Article
Presenting the COGNIFOG Framework: Architecture, Building Blocks and Road toward Cognitive Connectivity
by Toni Adame, Emna Amri, Grigoris Antonopoulos, Selma Azaiez, Alexandre Berne, Juan Sebastian Camargo, Harry Kakoulidis, Sofia Kleisarchaki, Alberto Llamedo, Marios Prasinos, Kyriaki Psara and Klym Shumaiev
Sensors 2024, 24(16), 5283; https://doi.org/10.3390/s24165283 - 15 Aug 2024
Cited by 1 | Viewed by 1993
Abstract
In the era of ubiquitous computing, the challenges imposed by the increasing demand for real-time data processing, security, and energy efficiency call for innovative solutions. The emergence of fog computing has provided a promising paradigm to address these challenges by bringing computational resources [...] Read more.
In the era of ubiquitous computing, the challenges imposed by the increasing demand for real-time data processing, security, and energy efficiency call for innovative solutions. The emergence of fog computing has provided a promising paradigm to address these challenges by bringing computational resources closer to data sources. Despite its advantages, the fog computing characteristics pose challenges in heterogeneous environments in terms of resource allocation and management, provisioning, security, and connectivity, among others. This paper introduces COGNIFOG, a novel cognitive fog framework currently under development, which was designed to leverage intelligent, decentralized decision-making processes, machine learning algorithms, and distributed computing principles to enable the autonomous operation, adaptability, and scalability across the IoT–edge–cloud continuum. By integrating cognitive capabilities, COGNIFOG is expected to increase the efficiency and reliability of next-generation computing environments, potentially providing a seamless bridge between the physical and digital worlds. Preliminary experimental results with a limited set of connectivity-related COGNIFOG building blocks show promising improvements in network resource utilization in a real-world-based IoT scenario. Overall, this work paves the way for further developments on the framework, which are aimed at making it more intelligent, resilient, and aligned with the ever-evolving demands of next-generation computing environments. Full article
(This article belongs to the Special Issue Wireless Sensor Networks: Signal Processing and Communications)
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13 pages, 3586 KiB  
Article
Manoeuvre Target Tracking in Wireless Sensor Networks Using Convolutional Bi-Directional Long Short-Term Memory Neural Networks and Extended Kalman Filtering
by Duo Peng, Kun Xie and Mingshuo Liu
Sensors 2024, 24(13), 4261; https://doi.org/10.3390/s24134261 - 30 Jun 2024
Cited by 1 | Viewed by 1152
Abstract
Aiming at the problem that traditional wireless sensor networks produce errors in the positioning and tracking of motorised targets due to noise interference, this paper proposes a motorised target tracking method with a convolutional bi-directional long and short-term memory neural network and extended [...] Read more.
Aiming at the problem that traditional wireless sensor networks produce errors in the positioning and tracking of motorised targets due to noise interference, this paper proposes a motorised target tracking method with a convolutional bi-directional long and short-term memory neural network and extended Kalman filtering, which is trained by using the simulated RSSI value and the actual target value of motorised targets collected from the convolutional bi-directional neural network to the sensor anchor node, so as to obtain a more accurate initial value of the manoeuvre target, and at the same time, the extended Kalman filtering method is used to accurately locate and track the real-time target, so as to obtain the accurate positioning and tracking information of the real-time target. Through experimental simulation, it can be seen that the algorithm proposed in this paper has good tracking effect in both linear manoeuvre target tracking scenarios and non-linear manoeuvre target tracking scenarios. Full article
(This article belongs to the Special Issue Wireless Sensor Networks: Signal Processing and Communications)
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17 pages, 618 KiB  
Article
Contention-Less Multi-Link Synchronous Transmission for Throughput Enhancement and Heterogeneous Fairness in Wi-Fi 7
by Lam Kwon and Eun-Chan Park
Sensors 2024, 24(11), 3642; https://doi.org/10.3390/s24113642 - 4 Jun 2024
Viewed by 1319
Abstract
Multi-link operation (MLO) is a new and essential mechanism of IEEE 802.11be Extremely High Throughput (Wi-Fi 7) that can increase throughput and decrease latency in Wireless Local Area Networks (WLANs). The MLO enables a Multi-Link Device (MLD) to perform Simultaneous Transmission and Reception [...] Read more.
Multi-link operation (MLO) is a new and essential mechanism of IEEE 802.11be Extremely High Throughput (Wi-Fi 7) that can increase throughput and decrease latency in Wireless Local Area Networks (WLANs). The MLO enables a Multi-Link Device (MLD) to perform Simultaneous Transmission and Reception (STR) in different frequency bands. However, not all MLDs can support STR due to cross-link or in-device coexistence interference, while an STR-unable MLD (NSTR-MLD) can transmit multiple frames simultaneously in more than two links. This study focuses on the problems when NSTR-MLDs share a link with Single-Link Devices (SLDs). We propose a Contention-Less Synchronous Transmission (CLST) mechanism to improve fairness between NSTR-MLDs and SLDs while increasing the total network throughput. The proposed mechanism classifies links as MLD Dominant Links (MDLs) and Heterogeneous Coexistence Links (HCLs). In the proposed mechanism, an NSTR-MLD obtains a Synchronous Transmission Token (STT) through a virtual channel contention in the HCL but does not actually transmit a frame in the HCL, which is compensated for by a synchronous transmission triggered in the MDL. Moreover, the CLST mechanism allows additional subsequent transmissions up to the accumulated STT without further contention. Extensive simulation results confirm the outstanding performance of the CLST mechanism in terms of total throughput and fairness compared to existing synchronous transmission mechanisms. Full article
(This article belongs to the Special Issue Wireless Sensor Networks: Signal Processing and Communications)
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