Advanced Wireless Sensor Networks: Applications, Challenges and Research Trends

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 10262

Special Issue Editors


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Guest Editor
Department of Electrical and Electronics Engineering, University of West Attica, 12244 Athens, Greece
Interests: algorithm design; approximation algorithms; algorithmic mechanism design; game theory, optimization algorithms for wireless sensor networks
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Special Issue Information

Dear Colleagues,

The ability of wireless sensor networks (WSNs) to support a practically endless variety of human activities places them among the most rapidly developing domains of technology with a continuously growing range of applications.

On the other hand, the utilization of WSNs is obstructed because of not only the limited resources of sensor nodes in terms of energy supply, memory, and processing, but also the inborn restrictions of wireless communications regarding power, speed, and the capacity of communication channels and their vulnerability to interferences and intrusion. Thus, numerous challenges arise on the subject of WSNs.

At the same time, emerging advances in various sectors of science and technology seem to be promising to support and enhance the operation of WSNs, thus triggering corresponding research trends.

This Special Issue aims to support research works related with the state of the art, standards, experimentations, implementations, applications, new research proposals, and case studies regarding WSNs. Invited papers have to be original and must not be published or be under review in any other conference or journal. Potential topics of this Special Issue include, but are not limited to, the following:

  • WSN applications;
  • WSNs for IoT;
  • WSNs for Industry 4.0;
  • Hardware platforms for WSNs;
  • Energy sustainability in WSNs;
  • Edge computing in WSNs;
  • Energy harvesting in WSNs;
  • Wireless energy transfer in WSNs;
  • Computational intelligence for WSNs;
  • Energy efficiency in WSNs;
  • Congestion avoidance and control in WSNs;
  • Connectivity maintenance in WSNs;
  • Coverage maximization in WSNs;
  • Multi-objective optimization in WSNs;
  • Routing protocols for WSNs;
  • Context awareness in WSNs;
  • Security and privacy in WSNs;
  • QoS in WSNs;
  • Data management in WSNs.

Prof. Dr. Dionisis Kandris
Dr. Eleftherios Anastasiadis
Guest Editors

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Published Papers (10 papers)

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Research

20 pages, 1314 KiB  
Article
WSN-Driven Advances in Soil Moisture Estimation: A Machine Learning Approach
by Tinku Singh, Majid Kundroo and Taehong Kim
Electronics 2024, 13(8), 1590; https://doi.org/10.3390/electronics13081590 - 22 Apr 2024
Viewed by 206
Abstract
Soil moisture estimation is crucial for agricultural productivity and environmental management. This study explores the integration of Wireless Sensor Networks (WSNs) with machine learning (ML) and deep learning (DL) techniques to optimize soil moisture estimation. By combining data from WSN nodes with satellite [...] Read more.
Soil moisture estimation is crucial for agricultural productivity and environmental management. This study explores the integration of Wireless Sensor Networks (WSNs) with machine learning (ML) and deep learning (DL) techniques to optimize soil moisture estimation. By combining data from WSN nodes with satellite and climate data, this research aims to enhance the accuracy and resolution of soil moisture estimation, enabling more effective agricultural planning, irrigation management, and environmental monitoring. Five ML models, including linear regression, support vector machines, decision trees, random forests, and long short-term memory networks (LSTM), are evaluated and compared using real-world data from multiple geographical regions, which includes a dataset from NASA’s SMAP project, supplemented by climate data, which employs both active and passive sensors for data collection. The outcomes demonstrate that the LSTM model consistently outperforms other ML algorithms across various evaluation metrics, highlighting the effectiveness of WSN-driven approaches to soil moisture estimation. The study contributes to the advancement of soil moisture monitoring technologies, offering insights into the potential of WSNs combined with ML and DL for sustainable agriculture and environmental management practices. Full article
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16 pages, 1428 KiB  
Article
Innovative Firmware Update Method to Microcontrollers during Runtime
by Bernardino Pinto Neves, Victor D. N. Santos and António Valente
Electronics 2024, 13(7), 1328; https://doi.org/10.3390/electronics13071328 - 01 Apr 2024
Viewed by 1120
Abstract
This article presents a new firmware update paradigm for optimising the procedure in microcontrollers. The aim is to allow updating during program execution, without interruptions or restarts, replacing only specific code segments. The proposed method uses static and absolute addresses to locate and [...] Read more.
This article presents a new firmware update paradigm for optimising the procedure in microcontrollers. The aim is to allow updating during program execution, without interruptions or restarts, replacing only specific code segments. The proposed method uses static and absolute addresses to locate and isolate the code segment to be updated. The work focuses on Microchip’s PIC18F27K42 microcontroller and includes an example of updating functionality without affecting ongoing applications. This approach is ideal for band limited channels, reducing the amount of data transmitted during the update process. It also allows incremental changes to the program code, preserving network capacity, and reduces the costs associated with data transfer, especially in firmware update scenarios using cellular networks. This ability to update the normal operation of the device, avoiding service interruption and minimising downtime, is of remarkable value. Full article
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17 pages, 4317 KiB  
Article
Time-Allocation Adaptive Data Rate: An Innovative Time-Managed Algorithm for Enhanced Long-Range Wide-Area Network Performance
by Kunzhu Wang, Kun Wang and Yongfeng Ren
Electronics 2024, 13(2), 434; https://doi.org/10.3390/electronics13020434 - 20 Jan 2024
Viewed by 658
Abstract
Currently, a variety of Low-Power Wide-Area Network (LPWAN) technologies offer diverse solutions for long-distance communication. Among these, Long-Range Wide-Area Network (LoRaWAN) has garnered considerable attention for its widespread applications in the Internet of Things (IoT). Nevertheless, LoRaWAN still faces the challenge of channel [...] Read more.
Currently, a variety of Low-Power Wide-Area Network (LPWAN) technologies offer diverse solutions for long-distance communication. Among these, Long-Range Wide-Area Network (LoRaWAN) has garnered considerable attention for its widespread applications in the Internet of Things (IoT). Nevertheless, LoRaWAN still faces the challenge of channel collisions when managing dense node communications, a significant bottleneck to its performance. Addressing this issue, this study has developed a novel “time allocation adaptive Data Rate” (TA-ADR) algorithm for network servers. This algorithm dynamically adjusts the spreading factor (SF) and transmission power (TP) of LoRa (Long Range) nodes and intelligently schedules transmission times, effectively reducing the risk of data collisions on the same frequency channel and significantly enhancing data transmission efficiency. Simulations in a dense LoRaWAN network environment, encompassing 1000 nodes within a 480 m × 480 m range, demonstrate that compared to the ADR+ algorithm, our proposed algorithm achieves substantial improvements of approximately 30.35% in data transmission rate, 24.57% in energy consumption, and 31.25% in average network throughput. Full article
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35 pages, 22277 KiB  
Article
Novel Hybrid SOR- and AOR-Based Multi-User Detection for Uplink M-MIMO B5G Systems
by Yung-Ping Tu, Pei-Shen Jian and Yung-Fa Huang
Electronics 2024, 13(1), 187; https://doi.org/10.3390/electronics13010187 - 31 Dec 2023
Viewed by 745
Abstract
The Internet of Things (IoT) is one of the most important wireless sensor network (WSN) applications in 5G systems and requires a large amount of wireless data transmission. Therefore, massive multiple-input multiple-output (M-MIMO) has become a crucial type of technology and trend in [...] Read more.
The Internet of Things (IoT) is one of the most important wireless sensor network (WSN) applications in 5G systems and requires a large amount of wireless data transmission. Therefore, massive multiple-input multiple-output (M-MIMO) has become a crucial type of technology and trend in the future of beyond fifth-generation (B5G) wireless network communication systems. However, as the number of antennas increases, this also causes a significant increase in complexity at the receiving end. This is a challenge that must be overcome. To reduce the BER, confine the computational complexity, and produce a form of detection suitable for 4G and B5G environments simultaneously, we propose a novel multi-user detection (MUD) scheme for the uplink of M-MIMO orthogonal frequency division multiplexing (OFDM) and universal filtered multi-carrier (UFMC) systems that combines the merits of successive over-relaxation (SOR) and accelerated over-relaxation (AOR) named mixed over-relaxation (MOR). Herein, we divide MOR into the initial and collaboration stages. The former will produce the appropriate initial parameters to improve feasibility and divergence risk. Then, the latter achieves rapid convergence and refinement performance through alternating iterations. The conducted simulations show that our proposed form of detection, compared with the BER performance of traditional SOR and AOR, can achieve 99.999% and 99.998% improvement, respectively, and keep the complexity at O(N2). It balances BER performance and complexity with fewer iterations. Full article
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16 pages, 2818 KiB  
Article
Q-Learning and Efficient Low-Quantity Charge Method for Nodes to Extend the Lifetime of Wireless Sensor Networks
by Kunpeng Xu, Zheng Li, Ao Cui, Shuqin Geng, Deyong Xiao, Xianhui Wang and Peiyuan Wan
Electronics 2023, 12(22), 4676; https://doi.org/10.3390/electronics12224676 - 17 Nov 2023
Cited by 1 | Viewed by 707
Abstract
With the rapid development of the Internet of Things (IoT), improving the lifetime of nodes and networks has become increasingly important. Most existing medium access control protocols are based on scheduling the standby and active periods of nodes and do not consider the [...] Read more.
With the rapid development of the Internet of Things (IoT), improving the lifetime of nodes and networks has become increasingly important. Most existing medium access control protocols are based on scheduling the standby and active periods of nodes and do not consider the alarm state. This paper proposes a Q-learning and efficient low-quantity charge (QL-ELQC) method for the smoke alarm unit of a power system to reduce the average current and to improve the lifetime of the wireless sensor network (WSN) nodes. Quantity charge models were set up, and the QL-ELQC method is based on the duty cycle of the standby and active times for the nodes and considers the relationship between the sensor data condition and the RF module that can be activated and deactivated only at a certain time. The QL-ELQC method effectively overcomes the continuous state–action space limitation of Q-learning using the state classification method. The simulation results reveal that the proposed scheme significantly improves the latency and energy efficiency compared with the existing QL-Load scheme. Moreover, the experimental results are consistent with the theoretical results. The proposed QL-ELQC approach can be applied in various scenarios where batteries cannot be replaced or recharged under harsh environmental conditions. Full article
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16 pages, 1920 KiB  
Article
Investigation of the Information Interaction of the Sensor Network End IoT Device and the Hub at the Transport Protocol Level
by Viacheslav Kovtun, Krzysztof Grochla and Konrad Połys
Electronics 2023, 12(22), 4662; https://doi.org/10.3390/electronics12224662 - 15 Nov 2023
Cited by 2 | Viewed by 792
Abstract
The study examines the process of information transfer between the sensor network end IoT device and the hub at the transport protocol level focused on using the 5G platform. The authors interpreted the researched process as a semi-Markov (focused on the dynamics of [...] Read more.
The study examines the process of information transfer between the sensor network end IoT device and the hub at the transport protocol level focused on using the 5G platform. The authors interpreted the researched process as a semi-Markov (focused on the dynamics of the size of the protocol sliding window) process with two nested Markov chains (the first characterizes the current size of the sliding window, and the second, the number of data blocks sent at the current value of this characteristic). As a result, a stationary distribution of the size of the sliding window was obtained both for the resulting semi-Markov process and for nested Markov chains, etc. A recursive approach to the calculation of the mentioned stationary distribution is formalized. This approach is characterized by linear computational complexity. Based on the obtained stationary distribution of the size of the sliding window, a distribution function is formulated that characterizes the bandwidth of the communication channel between the entities specified in the research object. Using the resulting mathematical apparatus, the Window Scale parameter of the TCP Westwood+ protocol was tuned. Testing has shown the superiority of the modified protocol over the basic versions of the BIC TCP, TCP Vegas, TCP NewReno, and TCP Veno protocols in conditions of data transfer between two points in the wireless sensor network environment. Full article
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23 pages, 5373 KiB  
Article
Information Fusion for 5G IoT: An Improved 3D Localisation Approach Using K-DNN and Multi-Layered Hybrid Radiomap
by Brahim El Boudani, Tasos Dagiuklas, Loizos Kanaris, Muddesar Iqbal and Christos Chrysoulas
Electronics 2023, 12(19), 4150; https://doi.org/10.3390/electronics12194150 - 05 Oct 2023
Viewed by 899
Abstract
Indoor positioning is a core enabler for various 5G identity and context-aware applications requiring precise and real-time simultaneous localisation and mapping (SLAM). In this work, we propose a K-nearest neighbours and deep neural network (K-DNN) algorithm to improve 3D indoor positioning. Our implementation [...] Read more.
Indoor positioning is a core enabler for various 5G identity and context-aware applications requiring precise and real-time simultaneous localisation and mapping (SLAM). In this work, we propose a K-nearest neighbours and deep neural network (K-DNN) algorithm to improve 3D indoor positioning. Our implementation uses a novel data-augmentation concept for the received signal strength (RSS)-based fingerprint technique to produce a 3D fused hybrid. In the offline phase, a machine learning (ML) approach is used to train a model on a radiomap dataset that is collected during the offline phase. The proposed algorithm is implemented on the constructed hybrid multi-layered radiomap to improve the 3D localisation accuracy. In our implementation, the proposed approach is based on the fusion of the prominent 5G IoT signals of Bluetooth Low Energy (BLE) and the ubiquitous WLAN. As a result, we achieved a 91% classification accuracy in 1D and a submeter accuracy in 2D. Full article
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19 pages, 8054 KiB  
Article
Latin-Square-Based Key Negotiation Protocol for a Group of UAVs
by Guangyue Kou, Guoheng Wei, Zhimin Yuan and Shilei Li
Electronics 2023, 12(14), 3131; https://doi.org/10.3390/electronics12143131 - 19 Jul 2023
Viewed by 751
Abstract
Unmanned aerial vehicle mobile ad hoc networks (UAVMANETs) formed by multi-UAV self-assembling networks have rapidly developed and been widely used in many industries in recent years. However, UAVMANETs suffer from the problems of complicated key negotiations and the difficult authentication of members’ identities [...] Read more.
Unmanned aerial vehicle mobile ad hoc networks (UAVMANETs) formed by multi-UAV self-assembling networks have rapidly developed and been widely used in many industries in recent years. However, UAVMANETs suffer from the problems of complicated key negotiations and the difficult authentication of members’ identities during key negotiations. To address these problems, this paper simplifies the authentication process by introducing a Latin square to improve the process of signature aggregation in the Boneh–Lynn–Shacham (BLS) signature scheme and to aggregate the keys negotiated via the elliptic-curve Diffie–Hellman (ECDH) protocol into new keys. As shown through security analysis and simulations, this scheme improves the efficiency of UAVMANET authentication and key negotiation while satisfying security requirements. Full article
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21 pages, 11509 KiB  
Article
Air Pollution Monitoring via Wireless Sensor Networks: The Investigation and Correction of the Aging Behavior of Electrochemical Gaseous Pollutant Sensors
by Ioannis Christakis, Odysseas Tsakiridis, Dionisis Kandris and Ilias Stavrakas
Electronics 2023, 12(8), 1842; https://doi.org/10.3390/electronics12081842 - 13 Apr 2023
Cited by 7 | Viewed by 2237
Abstract
The continuously growing human activity in large and densely populated cities pollutes air and consequently puts public health in danger. This is why air quality monitoring is necessary in all urban environments. However, the creation of dense air monitoring networks is extremely costly [...] Read more.
The continuously growing human activity in large and densely populated cities pollutes air and consequently puts public health in danger. This is why air quality monitoring is necessary in all urban environments. However, the creation of dense air monitoring networks is extremely costly because it requires the usage of a great number of air monitoring stations that are quite expensive. Instead, the usage of wireless sensor networks (WSNs) that incorporate low-cost electrochemical gas sensors provides an excellent alternative. Actually, sensors of this kind that are recommended for low-cost air quality monitoring applications may provide relatively precise measurements. However, the reliability of such sensors during their operational life is questionable. The research work presented in this article not only experimentally examined the correlation that exists between the validity of the measurements obtained from low-cost gas sensors and their aging, but also proposes novel corrective formulae for gas sensors of two different types (i.e., NO2, O3), which are aimed at alleviating the impact of aging on the accuracy of measurements. The following steps were conducted in order to both study and lessen the aging of electrochemical sensors: (i) a sensor network was developed to measure air quality at a place near official instruments that perform corresponding measurements; (ii) the collected data were compared to the corresponding recordings of the official instruments; (iii) calibration and compensation were performed using the electrochemical sensor vendor instructions; (iv) the divergence between the datasets was studied for various periods of time and the impact of aging was studied; (v) the compensation process was re-evaluated and new compensation coefficients were produced for all periods; (vi) the new compensation coefficients were used to shape formulae that automatically calculate the new coefficients with respect to the sensors’ aging; and (vii) the performance of the overall procedure was evaluated through the comparison of the final outcomes with real data. Full article
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14 pages, 2877 KiB  
Article
AoI-Bounded Scheduling for Industrial Wireless Sensor Networks
by Chenggen Pu, Han Yang, Ping Wang and Changjie Dong
Electronics 2023, 12(6), 1499; https://doi.org/10.3390/electronics12061499 - 22 Mar 2023
Cited by 1 | Viewed by 1362
Abstract
Age of information (AoI) is an emerging network metric that measures information freshness from an application layer perspective. It can evaluate the timeliness of information in industrial wireless sensor networks (IWSNs). Previous research has primarily focused on minimizing the long-term average AoI of [...] Read more.
Age of information (AoI) is an emerging network metric that measures information freshness from an application layer perspective. It can evaluate the timeliness of information in industrial wireless sensor networks (IWSNs). Previous research has primarily focused on minimizing the long-term average AoI of the entire system. However, in practical industrial applications, optimizing the average AoI does not guarantee that the peak AoI of each data packet is within a bounded interval. If the AoI of certain packets exceeds the predetermined threshold, it can have a significant impact on the stability of the industrial control system. Therefore, this paper studies the scheduling problem subject to a hard AoI performance requirement in IWSNs. First, we propose a low-complexity AoI-bounded scheduling algorithm for IWSNs that guarantees that the AoI of each packet is within a bounded interval. Then, we analyze the schedulability conditions of the algorithm and propose a method to decrease the peak AoI of nodes with higher AoI requirements. Finally, we present a numerical example that illustrates the proposed algorithm step by step. The results demonstrate the effectiveness of our algorithm, which can guarantee bounded AoI intervals (BAIs) for all nodes. Full article
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