Topic Editors

Dr. Alvaro Araujo Pinto
Department of Electronic Engineering, Universidad Politécnica de Madrid, 28040 Madrid, Spain
Dr. Hacene Fouchal
Département Mathématiques, Université de Reims Champagne-Ardenne, 51454 Reims, France

Wireless Sensor Networks

Abstract submission deadline
31 December 2022
Manuscript submission deadline
31 March 2023
Viewed by
43961

Topic Information

Dear Colleagues,

In the past couple of decades, wireless communications have expanded at an extraordinary rate, permeating every environment. The M2M paradigm is generally referred to by the more common term of the Internet of things (IoT), and both terms are sometimes used interchangeably. The IoT is generally described as a system of interconnected objects (things) that are capable of communicating with each other over the Internet without human active intervention. A key infrastructure that provides support to the IoT paradigm is wireless sensor networks (WSNs). WSNs consist of a set of spatially distributed electronic devices, commonly called nodes, deployed in an area of interest that collect and share information gained from their surroundings. Depending on the application, WSNs can have a varying number of sensor nodes, stretching from a few units to dozens or even hundreds.

The potential fields of application of WSNs are essentially aligned to those of the IoT paradigm, ranging from home automation to industry and manufacturing control, transportation, vehicular networking, agriculture, commerce, and health and body monitoring.

Nodes in a WSN are generally composed of at least four modules in charge of four main functions: sensing, communication, energy supply, and control.

Wireless Sensor Networks comprise a set of major components, including:

  • WSN platforms;
  • Wearable devices;
  • WSN data management;
  • Cross-layer design;
  • WSN architectures and protocol stack;
  • Authentication, data security, and protection;
  • WSN and artificial intelligence, edge computing;
  • Energy harvesting.

This Topic aims to collect the results of research in these Wireless Sensor Network scenarios, as well as the results of similar research. The submission of papers concerning areas with a strong connection to engineering and industrial and manufacturing applications is strongly encouraged.

Dr. Alvaro Araujo Pinto
Dr. Hacene Fouchal
Topic Editors

Keywords

  • wireless sensor networks
  • internet of things
  • IoT
  • artificial intelligence
  • smart sensors
  • intelligent sensors
  • WSAN
  • wireless sensor and actuator networks
  • wearables
  • energy harvesting
  • edge computing
  • cross-layer optimization
  • QoS for WSN
  • low-energy techniques
  • hardware platforms

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci
2.838 3.7 2011 17.4 Days 2300 CHF Submit
Electronics
electronics
2.690 3.7 2012 16.6 Days 2000 CHF Submit
Information
information
- 4.2 2010 18.9 Days 1400 CHF Submit
Journal of Sensor and Actuator Networks
jsan
- 6.9 2012 18.2 Days 1600 CHF Submit
Sensors
sensors
3.847 6.4 2001 16.2 Days 2400 CHF Submit
Chips
chips
- - 2022 15.0 days * 1000 CHF Submit

* Median value for all MDPI journals in the first half of 2022.


Preprints is a platform dedicated to making early versions of research outputs permanently available and citable. MDPI journals allow posting on preprint servers such as Preprints.org prior to publication. For more details about reprints, please visit https://www.preprints.org.

Published Papers (52 papers)

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Article
An On-Site-Based Opportunistic Routing Protocol for Scalable and Energy-Efficient Underwater Acoustic Sensor Networks
Appl. Sci. 2022, 12(23), 12482; https://doi.org/10.3390/app122312482 (registering DOI) - 06 Dec 2022
Viewed by 61
Abstract
With the advancements in wireless sensor networks and the Internet of Underwater Things (IoUT), underwater acoustic sensor networks (UASNs) have attracted much attention, which has also been widely used in marine engineering exploration and disaster prevention. However, UASNs still face many challenges, including [...] Read more.
With the advancements in wireless sensor networks and the Internet of Underwater Things (IoUT), underwater acoustic sensor networks (UASNs) have attracted much attention, which has also been widely used in marine engineering exploration and disaster prevention. However, UASNs still face many challenges, including high propagation latency, limited bandwidth, high energy consumption, and unreliable transmission, influencing the good quality of service (QoS). In this paper, we propose a routing protocol based on the on-site architecture (SROA) for UASNs to improve network scalability and energy efficiency. The on-site architecture adopted by SROA is different from most architectures in that the data center is deployed underwater, which makes the sink nodes closer to the data source. A clustering method is introduced in SROA, which makes the network adapt to the changes in the network scale and avoid single-point failure. Moreover, the Q-learning algorithm is applied to seek optimal routing policies, in which the characteristics of underwater acoustic communication such as residual energy, end-to-end delay, and link quality are considered jointly when constructing the reward function. Furthermore, the reduction of packet retransmissions and collisions is advocated using a waiting mechanism developed from opportunistic routing (OR). The SROA realizes opportunistic routing to choose candidate nodes and coordinate packet forwarding among candidate nodes. The scalability of the proposed routing protocols is also analyzed by varying the network size and transmission range. According to the evaluation results, with the network scale ranging from 100 to 500, the SROA outperforms the existing routing protocols, extensively decreasing energy consumption and end-to-end delay. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Communication
Wireless Heart Sensor for Capturing Cardiac Orienting Response for Prediction of Neurodevelopmental Delay in Infants
Sensors 2022, 22(23), 9140; https://doi.org/10.3390/s22239140 - 25 Nov 2022
Viewed by 277
Abstract
Early identification of infants at risk of neurodevelopmental delay is an essential public health aim. Such a diagnosis allows early interventions for infants that maximally take advantage of the neural plasticity in the developing brain. Using standardized physiological developmental tests, such as the [...] Read more.
Early identification of infants at risk of neurodevelopmental delay is an essential public health aim. Such a diagnosis allows early interventions for infants that maximally take advantage of the neural plasticity in the developing brain. Using standardized physiological developmental tests, such as the assessment of neurophysiological response to environmental events using cardiac orienting responses (CORs), is a promising and effective approach for early recognition of neurodevelopmental delay. Previous CORs have been collected on children using large bulky equipment that would not be feasible for widespread screening in routine clinical visits. We developed a portable wireless electrocardiogram (ECG) system along with a custom application for IOS tablets that, in tandem, can extract CORs with sufficient physiologic and timing accuracy to reflect the well-characterized ECG response to both auditory and visual stimuli. The sensor described here serves as an initial step in determining the extent to which COR tools are cost-effective for the early screening of children to determine who is at risk of developing neurocognitive deficits and may benefit from early interventions. We demonstrated that our approach, based on a wireless heartbeat sensor system and a custom mobile application for stimulus display and data recording, is sufficient to capture CORs from infants. The COR monitoring approach described here with mobile technology is an example of a desired standardized physiologic assessment that is a cost-and-time efficient, scalable method for early recognition of neurodevelopmental delay. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Blossom: Cluster-Based Routing for Preserving Privacy in Opportunistic Networks
J. Sens. Actuator Netw. 2022, 11(4), 75; https://doi.org/10.3390/jsan11040075 - 16 Nov 2022
Viewed by 328
Abstract
Opportunistic networks are an enabler technology for typologies without centralized infrastructure. Portable devices, such as wearable and embedded mobile systems, send relay messages to the communication range devices. One of the most critical challenges is to find the optimal route in these networks [...] Read more.
Opportunistic networks are an enabler technology for typologies without centralized infrastructure. Portable devices, such as wearable and embedded mobile systems, send relay messages to the communication range devices. One of the most critical challenges is to find the optimal route in these networks while at the same time preserving privacy for the participants of the network. Addressing this challenge, we presented a novel routing algorithm based on device clusters, reducing the overall message load and increasing network performance. At the same time, possibly identifying information of network nodes is eliminated by cloaking to meet privacy requirements. We evaluated our routing algorithm in terms of efficiency and privacy in opportunistic networks of traditional and structured cities, i.e., Venice and San Francisco by comparing our approach against the PRoPHET, First Contact, and Epidemic routing algorithms. In the San Francisco and Venice scenarios, Blossom improves messages delivery probability and outperforms PRoPHET, First Contact, and Epidemic by 46%, 100%, and 160% and by 67%, 78%, and 204%, respectively. In addition, the dropped messages probability in Blossom decreased 83% compared to PRoPHET and Epidemic in San Francisco and 91% compared to PRoPHET and Epidemic in Venice. Due to the small number of messages generated, the network overhead in this algorithm is close to zero. The network overhead can be significantly reduced by clustering while maintaining a reliable message delivery. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
An Adaptive and Spectrally Efficient Multi-Channel Medium Access Control Protocol for Dynamic Ad Hoc Networks
Sensors 2022, 22(22), 8666; https://doi.org/10.3390/s22228666 - 10 Nov 2022
Cited by 1 | Viewed by 493
Abstract
Medium access control (MAC) protocols in ad hoc networks have evolved from single-channel independent transmission mechanisms to multi-channel concurrent mechanisms to efficiently manage the demands placed on modern networks. The primary aim of this study is to compare the performance of popular multi-channel [...] Read more.
Medium access control (MAC) protocols in ad hoc networks have evolved from single-channel independent transmission mechanisms to multi-channel concurrent mechanisms to efficiently manage the demands placed on modern networks. The primary aim of this study is to compare the performance of popular multi-channel MAC (MMAC) protocols under saturated network traffic conditions and propose improvements to the protocols under these conditions. A novel, dynamically adaptive MMAC protocol was devised to take advantage of the performance capabilities of the evaluated protocols in changing wireless ad hoc network conditions. A simulation of the familiar MAC protocols was developed based on a validated simulation of the IEEE 802.11 standard. Further, the behaviors and performances of these protocols are compared against the proposed MMAC protocols with a varying number of ad hoc stations and concurrent wireless channels in terms of throughput, Jain’s fairness index, and channel access delay. The results show that the proposed MMAC protocol, labeled E-SA-MMAC, outperforms the existing protocols in throughput by up to 11.9% under a constrained number of channels and in channel access delays by up to 18.3%. It can be asserted from these observations that the proposed approach provides performance benefits against its peers under saturated traffic conditions and other factors, such as the number of available wireless channels, and is suitable for dynamic ad hoc network deployments. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Optimized Routing by Combining Grey Wolf and Dragonfly Optimization for Energy Efficiency in Wireless Sensor Networks
Appl. Sci. 2022, 12(21), 10948; https://doi.org/10.3390/app122110948 - 28 Oct 2022
Viewed by 304
Abstract
The rapid development of technology has resulted in numerous sensors and devices for performing measurements in an environment. Depending on the scale and application, the coverage and size of a wireless sensor network (WSN) is decided. During the implementation, the energy consumption and [...] Read more.
The rapid development of technology has resulted in numerous sensors and devices for performing measurements in an environment. Depending on the scale and application, the coverage and size of a wireless sensor network (WSN) is decided. During the implementation, the energy consumption and life of the nodes in the WSN are affected by the continuous usage. Hence, in this study, we aimed to improve the lifespan of the WSN and reduce energy consumption by the nodes during the data transfer using a hybrid approach. The hybrid approach combines Grey Wolf Optimization (GWO) and Dragonfly Optimization (DFO) for exploring a global solution and optimizing the local solution to find the optimum route for the data transfer between the target node and the control center. The results show that the proposed approach has effective energy consumption corresponding to the load applied. Our proposed system scored high in the average residual energy by the number of rounds compared to other methods such as k-means, LEACH-C, CHIRON, and Optimal-CBR. The first dead node was found after 500 rounds, showing that the proposed model has nodes with better reliability. It also showed a comparative analysis of the transmission rate of a packet concerning mobility speed among various methods. The proposed method has the highest ratio at all mobility speeds, i.e., 99.3, 99.1, 99, 98.8, and 98.6, and our proposed system has the lowest computational time of all the evaluated methods, 6 s. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Detection Performance Evaluation for Marine Wireless Sensor Networks
Electronics 2022, 11(20), 3367; https://doi.org/10.3390/electronics11203367 - 19 Oct 2022
Viewed by 348
Abstract
Detection performance evaluation is one of the inevitable problems for marine wireless sensor networks (MWSNs) deployed for target detection. However, it is a very complicated problem since it associates many different aspects, such as emitter power, range, radar cross-section, weather, geography, working mode, [...] Read more.
Detection performance evaluation is one of the inevitable problems for marine wireless sensor networks (MWSNs) deployed for target detection. However, it is a very complicated problem since it associates many different aspects, such as emitter power, range, radar cross-section, weather, geography, working mode, and so on. Targeting this problem, this paper incorporates the Poisson point process model into describing the ranges from sensors to targets. The relationship between sensors and a target is built from the perspective of detection probabilities. Then, a new consistent, conservative target detection probability evaluation is derived within a CFAR framework, and the further global detection probability of the whole MWSN on the target is developed. Additionally, the rationality of this modeling approach is demonstrated via simulation results, which is in accord with the actual situation. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
An Energy-Efficient Distributed Congestion Control Protocol for Wireless Multimedia Sensor Networks
Electronics 2022, 11(20), 3265; https://doi.org/10.3390/electronics11203265 - 11 Oct 2022
Viewed by 323
Abstract
Wireless multimedia sensor networks (WMSNs) generate a huge amount of multimedia data. Congestion is one of the most challenging open issues in WMSNs. Congestion causes low throughput, high packet loss and low energy efficiency. Congestion happens when the data carried by the network [...] Read more.
Wireless multimedia sensor networks (WMSNs) generate a huge amount of multimedia data. Congestion is one of the most challenging open issues in WMSNs. Congestion causes low throughput, high packet loss and low energy efficiency. Congestion happens when the data carried by the network surpasses the available capacity. This article presents an energy-efficient distributed congestion control protocol (DCCP) to mitigate congestion and improve end-to-end delay. Compared to the other protocols, the DCCP protocol proposed in this article can alleviate congestion by intelligently selecting the best path. First, congestion is detected by using two congestion indicators. Second, each node aggregates the received data and builds a traffic congestion map. The traffic congestion map is used to calculate the best path. Therefore, the traffic is balanced on different routes, which reduces the end-to-end delay. Finally, a rate controller is designed to prevent congestion in the network by sending a congestion notification message to a source node. After receiving a congestion notification message, the source node immediately adjusts its transmission rate. Experimental results based on raspberry pi sensor nodes show that the proposed DCCP protocol significantly improves network performance and is superior to existing modern congestion control protocols. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Investigation of Energy Cost of Data Compression Algorithms in WSN for IoT Applications
Sensors 2022, 22(19), 7685; https://doi.org/10.3390/s22197685 - 10 Oct 2022
Viewed by 526
Abstract
The exponential growth in remote sensing, coupled with advancements in integrated circuits (IC) design and fabrication technology for communication, has prompted the progress of Wireless Sensor Networks (WSN). WSN comprises of sensor nodes and hubs fit for detecting, processing, and communicating remotely. Sensor [...] Read more.
The exponential growth in remote sensing, coupled with advancements in integrated circuits (IC) design and fabrication technology for communication, has prompted the progress of Wireless Sensor Networks (WSN). WSN comprises of sensor nodes and hubs fit for detecting, processing, and communicating remotely. Sensor nodes have limited resources such as memory, energy and computation capabilities restricting their ability to process large volume of data that is generated. Compressing the data before transmission will help alleviate the problem. Many data compression methods have been proposed but mainly for image processing and a vast majority of them are not pertinent on sensor nodes because of memory impediment, energy utilization and handling speed. To overcome this issue, authors in this research have chosen Run Length Encoding (RLE) and Adaptive Huffman Encoding (AHE) data compression techniques as they can be executed on sensor nodes. Both RLE and AHE are capable of balancing compression ratio and energy utilization. In this paper, a hybrid method comprising RLE and AHE, named as H-RLEAHE, is proposed and further investigated for sensor nodes. In order to verify the efficacy of the data compression algorithms, simulations were run, and the results compared with the compression techniques employing RLE, AHE, H-RLEAHE, and without the use of any compression approach for five distinct scenarios. The results demonstrate the RLE’s efficiency, as it surpasses alternative data compression methods in terms of energy efficiency, network speed, packet delivery rate, and residual energy throughout all iterations. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Improving the Performance of Opportunistic Networks in Real-World Applications Using Machine Learning Techniques
J. Sens. Actuator Netw. 2022, 11(4), 61; https://doi.org/10.3390/jsan11040061 - 26 Sep 2022
Viewed by 477
Abstract
In Opportunistic Networks, portable devices such as smartphones, tablets, and wearables carried by individuals, can communicate and save-carry-forward their messages. The message transmission is often in the short range supported by communication protocols, such as Bluetooth, Bluetooth Low Energy, and Zigbee. These devices [...] Read more.
In Opportunistic Networks, portable devices such as smartphones, tablets, and wearables carried by individuals, can communicate and save-carry-forward their messages. The message transmission is often in the short range supported by communication protocols, such as Bluetooth, Bluetooth Low Energy, and Zigbee. These devices carried by individuals along with a city’s taxis and buses represent network nodes. The mobility, buffer size, message interval, number of nodes, and number of messages copied in such a network influence the network’s performance. Extending these factors can improve the delivery of the messages and, consequently, network performance; however, due to the limited network resources, it increases the cost and appends the network overhead. The network delivers the maximized performance when supported by the optimal factors. In this paper, we measured, predicted, and analyzed the impact of these factors on network performance using the Opportunistic Network Environment simulator and machine learning techniques. We calculated the optimal factors depending on the network features. We have used three datasets, each with features and characteristics reflecting different network structures. We collected the real-time GPS coordinates of 500 taxis in San Francisco, 320 taxis in Rome, and 196 public transportation buses in Münster, Germany, within 48 h. We also compared the network performance without selfish nodes and with 5%, 10%, 20%, and 50% selfish nodes. We suggested the optimized configuration under real-world conditions when resources are limited. In addition, we compared the performance of Epidemic, Prophet, and PPHB++ routing algorithms fed with the optimized factors. The results show how to consider the best settings for the network according to the needs and how self-sustaining nodes will affect network performance. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Applying an Integrated System of Cloud Management and Wireless Sensing Network to Green Smart Environments—Green Energy Monitoring on Campus
Sensors 2022, 22(17), 6521; https://doi.org/10.3390/s22176521 - 29 Aug 2022
Viewed by 539
Abstract
With increasing urbanization, the application of Internet of things (IoT) technology to city governance has become a trend in architecture, transportation, and healthcare management, making IoT applicable in various domains. This study used IoT to inspect green construction and adopted a front-end sensing [...] Read more.
With increasing urbanization, the application of Internet of things (IoT) technology to city governance has become a trend in architecture, transportation, and healthcare management, making IoT applicable in various domains. This study used IoT to inspect green construction and adopted a front-end sensing system, middle-end wireless transmission, and a back-end multifunctional system structure with cloud management. It integrated civil and electrical engineering to develop environmental monitoring technology and proposed a management information system for the implementation of green engineering. This study collected physical “measurements” of the greening environment on a campus. Ambient temperature and humidity were analyzed to explore the greening and energy-saving benefits of a green roof, a pervious road, and a photovoltaic roof. When the ambient temperature was below 25 °C, the solar panels had an insulation effect on the roof of the building during both 4:00–5:00 and 12:00–13:00, with an optimal insulation effect of 2.45 °C. When the ambient temperature was above 25 °C, the panels had a cooling effect on the roof of the building, whether during 4:00–5:00 or 12:00–13:00, with an optimal cooling effect of 5.77 °C. During the lower temperature period (4:00–5:00), the ecological terrace had an insulation effect on the space beneath, with an effect of approximately 1–3 °C and a mean insulation of 1.95 °C. During the higher temperature period (12:00–13:00), it presented a cooling effect on the space beneath, with an effect of approximately 0.5–9 °C and a mean cooling temperature of 5.16 °C. The cooling effect of the three greening areas on air and ground temperature decreased in the following order: pervious road > photovoltaic roof > ecological terrace. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Review
Fault Tolerance Structures in Wireless Sensor Networks (WSNs): Survey, Classification, and Future Directions
Sensors 2022, 22(16), 6041; https://doi.org/10.3390/s22166041 - 12 Aug 2022
Viewed by 756
Abstract
The Industrial Revolution 4.0 (IR 4.0) has drastically impacted how the world operates. The Internet of Things (IoT), encompassed significantly by the Wireless Sensor Networks (WSNs), is an important subsection component of the IR 4.0. WSNs are a good demonstration of an ambient [...] Read more.
The Industrial Revolution 4.0 (IR 4.0) has drastically impacted how the world operates. The Internet of Things (IoT), encompassed significantly by the Wireless Sensor Networks (WSNs), is an important subsection component of the IR 4.0. WSNs are a good demonstration of an ambient intelligence vision, in which the environment becomes intelligent and aware of its surroundings. WSN has unique features which create its own distinct network attributes and is deployed widely for critical real-time applications that require stringent prerequisites when dealing with faults to ensure the avoidance and tolerance management of catastrophic outcomes. Thus, the respective underlying Fault Tolerance (FT) structure is a critical requirement that needs to be considered when designing any algorithm in WSNs. Moreover, with the exponential evolution of IoT systems, substantial enhancements of current FT mechanisms will ensure that the system constantly provides high network reliability and integrity. Fault tolerance structures contain three fundamental stages: error detection, error diagnosis, and error recovery. The emergence of analytics and the depth of harnessing it has led to the development of new fault-tolerant structures and strategies based on artificial intelligence and cloud-based. This survey provides an elaborate classification and analysis of fault tolerance structures and their essential components and categorizes errors from several perspectives. Subsequently, an extensive analysis of existing fault tolerance techniques based on eight constraints is presented. Many prior studies have provided classifications for fault tolerance systems. However, this research has enhanced these reviews by proposing an extensively enhanced categorization that depends on the new and additional metrics which include the number of sensor nodes engaged, the overall fault-tolerant approach performance, and the placement of the principal algorithm responsible for eliminating network errors. A new taxonomy of comparison that also extensively reviews previous surveys and state-of-the-art scientific articles based on different factors is discussed and provides the basis for the proposed open issues. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Localization Approach for Underwater Sensors in the Magnetic Silencing Facility Based on Magnetic Field Gradients
Sensors 2022, 22(16), 6017; https://doi.org/10.3390/s22166017 - 12 Aug 2022
Viewed by 526
Abstract
Localization of the underwater magnetic sensor arrays plays a pivotal role in the magnetic silencing facility. A localization approach is proposed for underwater sensors based on the optimization of magnetic field gradients in the inverse problem of localization. In the localization system, a [...] Read more.
Localization of the underwater magnetic sensor arrays plays a pivotal role in the magnetic silencing facility. A localization approach is proposed for underwater sensors based on the optimization of magnetic field gradients in the inverse problem of localization. In the localization system, a solenoid coil carrying direct current serves as the magnetic source. By measuring the magnetic field generated by the magnetic source in different positions, an objective function is established. The position vector of the sensor is determined by a novel multi-swarm particle swarm optimization with dynamic learning strategy. Without the optimization of the magnetic source’s positions, the sensors’ positions, especially in the z-axis direction, struggle to meet the requested localization. A strategy is proposed to optimize the positions of the magnetic source based on magnetic field gradients in the three directions of x, y and z axes. Compared with the former method, the model experiments show that the proposed method could achieve a 10 cm location error for the position type 2 sensor and meet the request of localization. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Chaos-Enhanced Adaptive Hybrid Butterfly Particle Swarm Optimization Algorithm for Passive Target Localization
Sensors 2022, 22(15), 5739; https://doi.org/10.3390/s22155739 - 31 Jul 2022
Viewed by 509
Abstract
This paper considers the problem of finding the position of a passive target using noisy time difference of arrival (TDOA) measurements, obtained from multiple transmitters and a single receiver. The maximum likelihood (ML) estimator’s objective function is extremely nonlinear and non-convex, making it [...] Read more.
This paper considers the problem of finding the position of a passive target using noisy time difference of arrival (TDOA) measurements, obtained from multiple transmitters and a single receiver. The maximum likelihood (ML) estimator’s objective function is extremely nonlinear and non-convex, making it impossible to use traditional optimization techniques. In this regard, this paper proposes the chaos-enhanced adaptive hybrid butterfly particle swarm optimization algorithm, named CAHBPSO, as the hybridization of butterfly optimization (BOA) and particle swarm optimization (PSO) algorithms, to estimate passive target position. In the proposed algorithm, an adaptive strategy is employed to update the sensory fragrance of BOA algorithm, and chaos theory is incorporated into the inertia weight of PSO algorithm. Furthermore, an adaptive switch probability is employed to combine global and local search phases of BOA with the PSO algorithm. Additionally, the semidefinite programming is employed to convert the considered problem into a convex one. The statistical comparison on CEC2014 benchmark problems shows that the proposed algorithm provides a better performance compared to well-known algorithms. The CAHBPSO method surpasses the BOA, PSO and semidefinite programming (SDP) algorithms for a broad spectrum of noise, according to simulation findings, and achieves the Cramer–Rao lower bound (CRLB). Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Hybrid Clustering and Routing Algorithm with Threshold-Based Data Collection for Heterogeneous Wireless Sensor Networks
Sensors 2022, 22(15), 5471; https://doi.org/10.3390/s22155471 - 22 Jul 2022
Viewed by 543
Abstract
The concept of the internet of things (IoT) motivates us to connect bulk isolated heterogeneous devices to automate report generation without human interaction. Energy-efficient routing algorithms help to prolong the network lifetime of these energy-restricted smart devices that are connected by means of [...] Read more.
The concept of the internet of things (IoT) motivates us to connect bulk isolated heterogeneous devices to automate report generation without human interaction. Energy-efficient routing algorithms help to prolong the network lifetime of these energy-restricted smart devices that are connected by means of wireless sensor networks (WSNs). Current vendor-level advancements enable algorithm-level flexibility to design protocols to concurrently collect multiple application data while enforcing the reduction of energy expenditure to gain commercial success in the industrial stage. In this paper, we propose a hybrid clustering and routing algorithm with threshold-based data collection for heterogeneous wireless sensor networks. In our proposed model, homogeneous and heterogeneous nodes are deployed within specific regions. To reduce unnecessary data transmission, threshold-based conditions are presented to prevent unnecessary transmission when minor or no change is observed in the simulated and real-world applications. We further extend our proposed multi-hop model to achieve more network stability in dense and larger network areas. Our proposed model shows enhancement in terms of load balancing and end-to-end delay as compared to the other threshold-based energy-efficient routing protocols, such as the threshold-sensitive stable election protocol (TSEP), threshold distributed energy-efficient clustering (TDEEC), low-energy adaptive clustering hierarchy (LEACH), and energy-efficient sensor network (TEEN). Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks
Sensors 2022, 22(14), 5276; https://doi.org/10.3390/s22145276 - 14 Jul 2022
Cited by 1 | Viewed by 564
Abstract
In a wireless sensor network (WSN), reducing the energy consumption of battery-powered sensor nodes is key to extending their operating duration before battery replacement is required. Message bundling can save on the energy consumption of sensor nodes by reducing the number of message [...] Read more.
In a wireless sensor network (WSN), reducing the energy consumption of battery-powered sensor nodes is key to extending their operating duration before battery replacement is required. Message bundling can save on the energy consumption of sensor nodes by reducing the number of message transmissions. However, bundling a large number of messages could increase not only the end-to-end delays and message transmission intervals, but also the packet error rate (PER). End-to-end delays are critical in delay-sensitive applications, such as factory monitoring and disaster prevention. Message transmission intervals affect time synchronization accuracy when bundling includes synchronization messages, while an increased PER results in more message retransmissions and, thereby, consumes more energy. To address these issues, this paper proposes an optimal message bundling scheme based on an objective function for the total energy consumption of a WSN, which also takes into account the effects of packet retransmissions and, thereby, strikes the optimal balance between the number of bundled messages and the number of retransmissions given a link quality. The proposed optimal bundling is formulated as an integer nonlinear programming problem and solved using a self-adaptive global-best harmony search (SGHS) algorithm. The experimental results, based on the Cooja emulator of Contiki-NG, demonstrate that the proposed optimal bundling scheme saves up to 51.8% and 8.8% of the total energy consumption with respect to the baseline of no bundling and the state-of-the-art integer linear programming model, respectively. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Multi-Hop Routing Protocols for Oil Pipeline Leak Detection Systems
Electronics 2022, 11(13), 2078; https://doi.org/10.3390/electronics11132078 - 02 Jul 2022
Viewed by 627
Abstract
In recent years, various applications have emerged requiring linear topologies of wireless sensor networks (WSN). Such topologies are used in pipeline (water/oil/gas) monitoring systems. The linear structure has a significant impact on network performance in terms of delay, throughput, and power consumption. Regarding [...] Read more.
In recent years, various applications have emerged requiring linear topologies of wireless sensor networks (WSN). Such topologies are used in pipeline (water/oil/gas) monitoring systems. The linear structure has a significant impact on network performance in terms of delay, throughput, and power consumption. Regarding communication efficiency, routing protocols play a critical role, considering the special requirements of linear topology and energy resources. Therefore, the challenge is to design effective routing protocols that can address the diverse requirements of the monitoring system. In this paper, we present various wireless communication technologies and existing leak detection systems. We review different routing protocols focusing on multi-hop hierarchical protocols, highlighting the limitations and design issues related to packet routing in linear pipeline leak detection networks. Additionally, we present a LoRa multi-hop model for monitoring aboveground oil pipelines. A set of model parameters are identified such as the distance between sensors. In addition, the paper determines some calculations to estimate traffic congestion and energy consumption. Several alternative model designs are investigated. The model is evaluated using different multi-hop communication scenarios, and we compare the data rate and energy to provide an energy-efficient and low-cost leak detection system. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Towards Self-Powered WSN: The Design of Ultra-Low-Power Wireless Sensor Transmission Unit Based on Indoor Solar Energy Harvester
Electronics 2022, 11(13), 2077; https://doi.org/10.3390/electronics11132077 - 02 Jul 2022
Cited by 1 | Viewed by 595
Abstract
The current revolution in communication and information technology is facilitating the Internet of Things (IoT) infrastructure. Wireless Sensor Networks (WSN) are a broad category of IoT applications. However, power management in WSN poses a significant challenge when the WSN is required to operate [...] Read more.
The current revolution in communication and information technology is facilitating the Internet of Things (IoT) infrastructure. Wireless Sensor Networks (WSN) are a broad category of IoT applications. However, power management in WSN poses a significant challenge when the WSN is required to operate for a long duration without the presence of a consistent power source. In this paper, we develop a batteryless, ultra-low-power Wireless Sensor Transmission Unit (WSTx) depending on the solar-energy harvester and LoRa technology. We investigate the feasibility of harvesting ambient indoor light using polycrystalline photovoltaic (PV) cells with a maximum power of 1.4 mW. The study provides comprehensive power management design details and a description of the anticipated challenges. The measured power consumption of the developed WSTx was 0.02109 mW during the sleep mode and 11.1 mW during the operation mode. The harvesting system can harvest energy up to 1.2 mW per second, where the harvested energy can power the WSTx for six hours with a maximum power efficiency of 85.714%. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
HERO: Hybrid Effortless Resilient Operation Stations for Flash Flood Early Warning Systems
Sensors 2022, 22(11), 4108; https://doi.org/10.3390/s22114108 - 28 May 2022
Viewed by 690
Abstract
Floods are the most frequent type of natural disaster. Flash floods are one of the most common types of floods, caused by rapid and excessive rainfall. Normally, when a flash flood occurs, the water of the upstream river increases rapidly and flows to [...] Read more.
Floods are the most frequent type of natural disaster. Flash floods are one of the most common types of floods, caused by rapid and excessive rainfall. Normally, when a flash flood occurs, the water of the upstream river increases rapidly and flows to the downstream watersheds. The overflow of water increasingly submerges villages in the drainage basins. Flash flood early warning systems are required to mitigate losses. Water level monitoring stations can be installed at upstream river areas. However, telemetry stations face several challenges because the upstream river areas are far away and lack of public utilities (e.g., electric power and telephone lines). This research proposes hybrid effortless resilient operation stations, named HERO stations, in the flash flood early warning system. The HERO station was designed and developed with a modular design concept to be effortlessly customized and maintained. The HERO station adapts its working operation against the environmental changes to maintain a long working period with high data sensing accuracy. Moreover, the HERO station can switch its communication mode between the centralized and decentralized communication modes to increase availability. The network of the HERO stations has already been deployed in the northern part of Thailand. It results in improvements of the telemetry station’s availability. The HERO stations can adapt to environmental changes. The flash flood early warning messages can be disseminated to the villagers to increase the flood preparation time and to reduce flash flood damage. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Long-Range Low-Power Multi-Hop Wireless Sensor Network for Monitoring the Vibration Response of Long-Span Bridges
Sensors 2022, 22(10), 3916; https://doi.org/10.3390/s22103916 - 22 May 2022
Viewed by 777
Abstract
Recently, vibration-based monitoring technologies have become extremely popular, providing effective tools to assess the health condition and evaluate the structural integrity of civil structures and infrastructures in real-time. In this context, battery-operated wireless sensors allow us to stop using wired sensor networks, providing [...] Read more.
Recently, vibration-based monitoring technologies have become extremely popular, providing effective tools to assess the health condition and evaluate the structural integrity of civil structures and infrastructures in real-time. In this context, battery-operated wireless sensors allow us to stop using wired sensor networks, providing easy installation processes and low maintenance costs. Nevertheless, wireless transmission of high-rate data such as structural vibration consumes considerable power. Consequently, these wireless networks demand frequent battery replacement, which is problematic for large structures with poor accessibility, such as long-span bridges. This work proposes a low-power multi-hop wireless sensor network suitable for monitoring large-sized civil infrastructures to handle this problem. The proposed network employs low-power wireless devices that act in the sub-GHz band, permitting long-distance data transmission and communication surpassing 1 km. Data collection over vast areas is accomplished via multi-hop communication, in which the sensor data are acquired and re-transmitted by neighboring sensors. The communication and transmission times are synchronized, and time-division communication is executed, which depends on the wireless devices to sleep when the connection is not necessary to consume less power. An experimental field test is performed to evaluate the reliability and accuracy of the designed wireless sensor network to collect and capture the acceleration response of the long-span Manhattan Bridge. Thanks to the high-quality monitoring data collected with the developed low-power wireless sensor network, the natural frequencies and mode shapes were robustly recognized. The monitoring tests also showed the benefits of the presented wireless sensor system concerning the installation and measuring operations. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
A Wireless Underground Sensor Network Field Pilot for Agriculture and Ecology: Soil Moisture Mapping Using Signal Attenuation
Sensors 2022, 22(10), 3913; https://doi.org/10.3390/s22103913 - 21 May 2022
Viewed by 1194
Abstract
Wireless Underground Sensor Networks (WUSNs) that collect geospatial in situ sensor data are a backbone of internet-of-things (IoT) applications for agriculture and terrestrial ecology. In this paper, we first show how WUSNs can operate reliably under field conditions year-round and at the same [...] Read more.
Wireless Underground Sensor Networks (WUSNs) that collect geospatial in situ sensor data are a backbone of internet-of-things (IoT) applications for agriculture and terrestrial ecology. In this paper, we first show how WUSNs can operate reliably under field conditions year-round and at the same time be used for determining and mapping soil conditions from the buried sensor nodes. We demonstrate the design and deployment of a 23-node WUSN installed at an agricultural field site that covers an area with a 530 m radius. The WUSN has continuously operated since September 2019, enabling real-time monitoring of soil volumetric water content (VWC), soil temperature (ST), and soil electrical conductivity. Secondly, we present data collected over a nine-month period across three seasons. We evaluate the performance of a deep learning algorithm in predicting soil VWC using various combinations of the received signal strength (RSSI) from each buried wireless node, above-ground pathloss, the distance between wireless node and receive antenna (D), ST, air temperature (AT), relative humidity (RH), and precipitation as input parameters to the model. The AT, RH, and precipitation were obtained from a nearby weather station. We find that a model with RSSI, D, AT, ST, and RH as inputs was able to predict soil VWC with an R2 of 0.82 for test datasets, with a Root Mean Square Error of ±0.012 (m3/m3). Hence, a combination of deep learning and other easily available soil and climatic parameters can be a viable candidate for replacing expensive soil VWC sensors in WUSNs. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
REIP: A Reconfigurable Environmental Intelligence Platform and Software Framework for Fast Sensor Network Prototyping
Sensors 2022, 22(10), 3809; https://doi.org/10.3390/s22103809 - 17 May 2022
Viewed by 914
Abstract
Sensor networks have dynamically expanded our ability to monitor and study the world. Their presence and need keep increasing, and new hardware configurations expand the range of physical stimuli that can be accurately recorded. Sensors are also no longer simply recording the data, [...] Read more.
Sensor networks have dynamically expanded our ability to monitor and study the world. Their presence and need keep increasing, and new hardware configurations expand the range of physical stimuli that can be accurately recorded. Sensors are also no longer simply recording the data, they process it and transform into something useful before uploading to the cloud. However, building sensor networks is costly and very time consuming. It is difficult to build upon other people’s work and there are only a few open-source solutions for integrating different devices and sensing modalities. We introduce REIP, a Reconfigurable Environmental Intelligence Platform for fast sensor network prototyping. REIP’s first and most central tool, implemented in this work, is an open-source software framework, an SDK, with a flexible modular API for data collection and analysis using multiple sensing modalities. REIP is developed with the aim of being user-friendly, device-agnostic, and easily extensible, allowing for fast prototyping of heterogeneous sensor networks. Furthermore, our software framework is implemented in Python to reduce the entrance barrier for future contributions. We demonstrate the potential and versatility of REIP in real world applications, along with performance studies and benchmark REIP SDK against similar systems. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Self-Stabilizing Capacitated Vertex Cover Algorithms for Internet-of-Things-Enabled Wireless Sensor Networks
Sensors 2022, 22(10), 3774; https://doi.org/10.3390/s22103774 - 16 May 2022
Viewed by 812
Abstract
Wireless sensor networks (WSNs) achieving environmental sensing are fundamental communication layer technologies in the Internet of Things. Battery-powered sensor nodes may face many problems, such as battery drain and software problems. Therefore, the utilization of self-stabilization, which is one of the fault-tolerance techniques, [...] Read more.
Wireless sensor networks (WSNs) achieving environmental sensing are fundamental communication layer technologies in the Internet of Things. Battery-powered sensor nodes may face many problems, such as battery drain and software problems. Therefore, the utilization of self-stabilization, which is one of the fault-tolerance techniques, brings the network back to its legitimate state when the topology is changed due to node leaves. In this technique, a scheduler decides on which nodes could execute their rules regarding spatial and temporal properties. A useful graph theoretical structure is the vertex cover that can be utilized in various WSN applications such as routing, clustering, replica placement and link monitoring. A capacitated vertex cover is the generalized version of the problem which restricts the number of edges covered by a vertex by applying a capacity constraint to limit the covered edge count. In this paper, we propose two self-stabilizing capacitated vertex cover algorithms for WSNs. To the best of our knowledge, these algorithms are the first attempts in this manner. The first algorithm is stabilized under an unfair distributed scheduler (that is, the scheduler which does not grant all enabled nodes to make their moves but guarantees the global progress of the system) at most O(n2) step, where n is the count of nodes. The second algorithm assumes 2-hop (degree 2) knowledge about the network and runs under the unfair scheduler, which subsumes the synchronous and distributed fair scheduler and stabilizes itself after O(n) moves in O(n) step, which is acceptable for most WSN setups. We theoretically analyze the algorithms to provide proof of correctness and their step complexities. Moreover, we provide simulation setups by applying IRIS sensor node parameters and compare our algorithms with their counterparts. The gathered measurements from the simulations revealed that the proposed algorithms are faster than their competitors, use less energy and offer better vertex cover solutions. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Multi-AP and Test Point Accuracy of the Results in WiFi Indoor Localization
Sensors 2022, 22(10), 3709; https://doi.org/10.3390/s22103709 - 12 May 2022
Cited by 1 | Viewed by 929
Abstract
WiFi-based indoor positioning has attracted intensive research activities. While localization accuracy is steadily improving due to the application of advanced algorithms, the factors that affect indoor localization accuracy have not been sufficiently understood. Most localization algorithms used in changing indoor spaces are Angle-of-Arrival [...] Read more.
WiFi-based indoor positioning has attracted intensive research activities. While localization accuracy is steadily improving due to the application of advanced algorithms, the factors that affect indoor localization accuracy have not been sufficiently understood. Most localization algorithms used in changing indoor spaces are Angle-of-Arrival (AoA) based, and they deploy the conventional MUSIC algorithm. The localization accuracy can be achieved by algorithm improvements or joint localization that deploys multiple Access Points (APs). We performed an experiment that assessed the Test Point (TP) accuracy and distribution of results in a complex environment. The testing space was a 290 m2 three-room environment with three APs with 38 TPs. The joint localization using three APs was performed in the same test space. We developed and implemented a new algorithm for improved accuracy of joint localization. We analyzed the statistical characteristics of the results based on each TP and show that the local space-dependent factors are the key factors for localization accuracy. The most important factors that cause errors are distance, obstacles, corner locations, the location of APs, and the angular orientation of the antenna array. Compared with the well-known SpotFi algorithm, we achieved a mean accuracy (across all TPs) improvement of 46%. The unbiased joint localization median accuracy improved by 20% as compared to the best individual localization. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
A Mathematical-Based Model for Estimating the Path Duration of the DSDV Routing Protocol in MANETs
J. Sens. Actuator Netw. 2022, 11(2), 23; https://doi.org/10.3390/jsan11020023 - 12 May 2022
Viewed by 1185
Abstract
Mobile Ad Hoc Networks (MANETs) are kind of wireless networks where the nodes move in decentralized environments with a highly dynamic infrastructure. Many well-known routing protocols have been proposed, with each having its own design mechanism and its own strengths and weaknesses and [...] Read more.
Mobile Ad Hoc Networks (MANETs) are kind of wireless networks where the nodes move in decentralized environments with a highly dynamic infrastructure. Many well-known routing protocols have been proposed, with each having its own design mechanism and its own strengths and weaknesses and most importantly, each protocol being mainly designed for specific applications and scenarios. Most of the research studies in this field used simulation testbeds to analyze routing protocols. Very few contributions suggested the use of analytical studies and mathematical approaches to model some of the existing routing protocols. In this research, we have built a comprehensive mathematical-based model to analyze the Destination-Sequenced Distance Vector protocol (DSDV), one of the main widely deployed proactive protocols and studied its performance on estimating the path duration based on the concepts of the probability density function and the expected values to find the best approximation values in real scenarios. We have tested the validity of the proposed model using simulation scenarios implemented by the Network Simulator tool (NS3). The results extracted from both the mathematical model and the simulation have shown that the path duration is inversely proportional to both the speed of the node and the hop count. Furthermore, it had shown that the path duration estimated from the DSDV protocol is less than the actual path duration, due to the implementation of the settling time concept and keeping the “periodic routes’ update” parameter at a constant level, despite the fact that the node’s speed reduces the effective path utilization. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Review
Technological Requirements and Challenges in Wireless Body Area Networks for Health Monitoring: A Comprehensive Survey
Sensors 2022, 22(9), 3539; https://doi.org/10.3390/s22093539 - 06 May 2022
Cited by 2 | Viewed by 1230
Abstract
With the rapid growth in healthcare demand, an emergent, novel technology called wireless body area networks (WBANs) have become promising and have been widely used in the field of human health monitoring. A WBAN can collect human physical parameters through the medical sensors [...] Read more.
With the rapid growth in healthcare demand, an emergent, novel technology called wireless body area networks (WBANs) have become promising and have been widely used in the field of human health monitoring. A WBAN can collect human physical parameters through the medical sensors in or around the patient’s body to realize real-time continuous remote monitoring. Compared to other wireless transmission technologies, a WBAN has more stringent technical requirements and challenges in terms of power efficiency, security and privacy, quality of service and other specifications. In this paper, we review the recent WBAN medical applications, existing requirements and challenges and their solutions. We conducted a comprehensive investigation of WBANs, from the sensor technology for the collection to the wireless transmission technology for the transmission process, such as frequency bands, channel models, medium access control (MAC) and networking protocols. Then we reviewed its unique safety and energy consumption issues. In particular, an application-specific integrated circuit (ASIC)-based WBAN scheme is presented to improve its security and privacy and achieve ultra-low energy consumption. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Design and Implementation of a Multi-Hop Real-Time LoRa Protocol for Dynamic LoRa Networks
Sensors 2022, 22(9), 3518; https://doi.org/10.3390/s22093518 - 05 May 2022
Cited by 4 | Viewed by 730
Abstract
Recently, LoRa (Long Range) technology has been drawing attention in various applications due to its long communication range and high link reliability. However, in industrial environments, these advantages are often compromised by factors such as node mobility, signal attenuation due to various obstacles, [...] Read more.
Recently, LoRa (Long Range) technology has been drawing attention in various applications due to its long communication range and high link reliability. However, in industrial environments, these advantages are often compromised by factors such as node mobility, signal attenuation due to various obstacles, and link instability due to external signal interference. In this paper, we propose a new multi-hop LoRa protocol that can provide high reliability for data transmission by overcoming those factors in dynamic LoRa networks. This study extends the previously proposed two-hop real-time LoRa (Two-Hop RT-LoRa) protocol to address technical aspects of dynamic multi-hop networks, such as automatic configuration of multi-hop LoRa networks, dynamic topology management, and updating of real-time slot schedules. It is shown by simulation that the proposed protocol achieves high reliability of over 97% for mobile nodes and generates low control overhead in topology management and schedule updates. The protocol was also evaluated in various campus deployment scenarios. According to experiments, it could achieve high packet delivery rates of over 97% and 95%, respectively, for 1-hop nodes and 2-hop nodes against node mobility. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Wake-Up Receiver-Based Routing for Clustered Multihop Wireless Sensor Networks
Sensors 2022, 22(9), 3254; https://doi.org/10.3390/s22093254 - 23 Apr 2022
Cited by 1 | Viewed by 882
Abstract
The Wireless Sensor Network (WSN) is one of the most promising solutions for the supervision of multiple phenomena and for the digitisation of the Internet of Things (IoT). The Wake-up Receiver (WuRx) is one of the most trivial and effective solutions for energy-constrained [...] Read more.
The Wireless Sensor Network (WSN) is one of the most promising solutions for the supervision of multiple phenomena and for the digitisation of the Internet of Things (IoT). The Wake-up Receiver (WuRx) is one of the most trivial and effective solutions for energy-constrained networks. This technology allows energy-autonomous on-demand communication for continuous monitoring instead of the conventional radio. The routing process is one of the most energy and time-consuming processes in WSNs. It is, hence, crucial to conceive an energy-efficient routing process. In this paper, we propose a novel Wake-up Receiver-based routing protocol called Clustered WuRx based on Multicast wake-up (CWM), which ensures energy optimisation and time-efficiency at the same time for indoor scenarios. In our proposed approach, the network is divided into clusters. Each Fog Node maintains the routes from each node in its cluster to it. When a sink requires information from a given node, it’s corresponding Fog Node uses a multicast wake-up mechanism to wake up the intended node and all the intermediate nodes that will be used in the routing process simultaneously. Measurement results demonstrate that our proposed approach exhibits higher energy efficiency and has drastic performance improvements in the delivery delay compared with other routing protocols. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Stochastic Network Calculus-Aided Delay Analysis of Wireless-Power Line Mixed Networks
Electronics 2022, 11(9), 1326; https://doi.org/10.3390/electronics11091326 - 22 Apr 2022
Viewed by 449
Abstract
In this paper, we investigate the delay performance of a wireless-power line mixed network via a stochastic network calculus (SNC)-based approach. The data transmission in this mixed network is modeled by a two-stage tandem queue, wherein the data is first relayed through a [...] Read more.
In this paper, we investigate the delay performance of a wireless-power line mixed network via a stochastic network calculus (SNC)-based approach. The data transmission in this mixed network is modeled by a two-stage tandem queue, wherein the data is first relayed through a wireless fading channel and then transmitted over a power line communication (PLC) system. The Rayleigh fading captures the wireless fading channel; whereas, the PLC channel gain is characterized by the log-normal distribution. The statistical characteristics of the service processes of both the wireless channel and PLC channel are derived. With any given traffic arrival and the service capability derived, the delay can be easily bounded via SNC. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
A Novel Distributed Media Caching Technique for Seamless Video Streaming in Multi-Access Edge Computing Networks
Appl. Sci. 2022, 12(9), 4205; https://doi.org/10.3390/app12094205 - 21 Apr 2022
Viewed by 720
Abstract
Online video is anticipated to be the largest fraction of all mobile network traffic aside from the huge processing tasks imposed on networks by the billions of IoT devices, causing unprecedented challenges to the current network architecture. Edge caching has been proposed as [...] Read more.
Online video is anticipated to be the largest fraction of all mobile network traffic aside from the huge processing tasks imposed on networks by the billions of IoT devices, causing unprecedented challenges to the current network architecture. Edge caching has been proposed as a highly promising technology to overcome this challenge by placing computational and data storage resources at the network edge to reduce latency and backhaul traffic. However, the edge resources are heavily constrained in their storage and computational capacities as large-scale deployments mean fairly distributing resources across the network. Addressing this limitation, we propose an edge video caching scheme that dynamically caches the first part of popularity-ranked video files on Multi-Edge Computing Access Node (MAN) servers envisioned to achieve higher cache hit ratios, lower latencies, and lower backhaul traffic. The concept of Regionally Organized Clouds (ROCs) with sufficient resources for file caching and compute-intensive tasks was introduced, and a formulation of the edge caching problem as an Integer Linear Programming (ILP) problem was made. Additionally, this study proposes a file view-time threshold for each cached video aimed at reducing the resource wastage caused when buffered contents are abandoned. Comparative evaluations of the proposed show its excellent performance over FIFO, Greedy, LFRU and TLRU schemes. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Wireless Lan Performance Enhancement Using Double Deep Q-Networks
Appl. Sci. 2022, 12(9), 4145; https://doi.org/10.3390/app12094145 - 20 Apr 2022
Cited by 1 | Viewed by 781
Abstract
Due to the exponential growth in the use of Wi-Fi networks, it is necessary to study its usage pattern in dense environments for which the legacy IEEE 802.11 MAC (Medium Access Control) protocol was not specially designed. Although 802.11ax aims to improve Wi-Fi [...] Read more.
Due to the exponential growth in the use of Wi-Fi networks, it is necessary to study its usage pattern in dense environments for which the legacy IEEE 802.11 MAC (Medium Access Control) protocol was not specially designed. Although 802.11ax aims to improve Wi-Fi performance in dense scenarios due to modifications in the physical layer (PHY), however, MAC layer operations remain unchanged, and are not capable enough to provide stable performance in dense scenarios. Potential applications of Deep Learning (DL) to Media Access Control (MAC) layer of WLAN has now been recognized due to their unique features. Deep Reinforcement Learning (DRL) is a technique focused on behavioral sensitivity and control philosophy. In this paper, we have proposed an algorithm for setting optimal contention window (CW) under different network conditions called DRL-based Contention Window Optimization (DCWO). The proposed algorithm operates in three steps. In the initial step, Wi-Fi is being controlled by the 802.11 standards. In the second step, the agent makes the decisions concerning the value of CW after the TRAIN procedure for the proposed algorithm. The final phase begins after the training, defined by a time duration specified by the user. Now, the agent is fully trained, and no updates will be no longer received. Now the CW is updated via the OPTIMIZE process of DCWO. We have selected total network throughput, instantaneous network throughput, fairness index, and cumulative reward, and compared our proposed scheme DCWO with the Centralized Contention window Optimization with DRL (CCOD). Simulation results show that DCWO with Double Deep Q-Networks (DDQN) performs better than CCOD with (i) Deep Deterministic Policy Gradient (DDPG) and (ii) Deep Q-Network (DQN). More specifically, DCWO with DDQN gives on average 28% and 23% higher network throughput than CCOD in static and dynamic scenarios. Whereas in terms of instantaneous network throughput DCWO gives around 10% better results than the CCOD. DCWO achieves almost near to optimal fairness in static scenarios and better than DQN and DDPG with CCOD in dynamic scenarios. Similarly, while the cumulative reward achieved by DCWO is almost the same with CCOD with DDPG, the uptrend of DCWO is still encouraging. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
FPGA-Based Autonomous GPS-Disciplined Oscillatorsfor Wireless Sensor Network Nodes
Sensors 2022, 22(9), 3135; https://doi.org/10.3390/s22093135 - 20 Apr 2022
Cited by 2 | Viewed by 831
Abstract
Numerous devices in distributed wireless sensor arrays require a high-accuracy timing reference. Although the GPS-disciplined oscillators have been developed for decades, the hardware design still has performance limitations. In this context, we present the hardware implementation for a GPS-disciplined oscillator with an automatic [...] Read more.
Numerous devices in distributed wireless sensor arrays require a high-accuracy timing reference. Although the GPS-disciplined oscillators have been developed for decades, the hardware design still has performance limitations. In this context, we present the hardware implementation for a GPS-disciplined oscillator with an automatic adaptive drift correction algorithm, which is implemented in a low-cost, high-speed field-programmable gate array (FPGA) device. The system design and the hardware implementation are presented to demonstrate the advantages of the proposed oscillator. To verify this oscillator in real-time applications, we tested the device in multiple environments and compared it to state-of-the-art designs. The experimental results showed that our proposed device has a low cost and high performance. This device can achieve less than 80 ns and 356 ns in 1PPS signal drift in the indoor environment test and the outdoor environment test, respectively, after 24 h of working without a GPS signal. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
An Intra-Vehicular Wireless Multimedia Sensor Network for Smartphone-Based Low-Cost Advanced Driver-Assistance Systems
Sensors 2022, 22(8), 3026; https://doi.org/10.3390/s22083026 - 15 Apr 2022
Cited by 2 | Viewed by 935
Abstract
Advanced driver-assistance system(s) (ADAS) are more prevalent in high-end vehicles than in low-end vehicles. Wired solutions of vision sensors in ADAS already exist, but are costly and do not cater for low-end vehicles. General ADAS use wired harnessing for communication; this approach eliminates [...] Read more.
Advanced driver-assistance system(s) (ADAS) are more prevalent in high-end vehicles than in low-end vehicles. Wired solutions of vision sensors in ADAS already exist, but are costly and do not cater for low-end vehicles. General ADAS use wired harnessing for communication; this approach eliminates the need for cable harnessing and, therefore, the practicality of a novel wireless ADAS solution was tested. A low-cost alternative is proposed that extends a smartphone’s sensor perception, using a camera-based wireless sensor network. This paper presents the design of a low-cost ADAS alternative that uses an intra-vehicle wireless sensor network structured by a Wi-Fi Direct topology, using a smartphone as the processing platform. The proposed system makes ADAS features accessible to cheaper vehicles and investigates the possibility of using a wireless network to communicate ADAS information in a intra-vehicle environment. Other ADAS smartphone approaches make use of a smartphone’s onboard sensors; however, this paper shows the application of essential ADAS features developed on the smartphone’s ADAS application, carrying out both lane detection and collision detection on a vehicle by using wireless sensor data. A smartphone’s processing power was harnessed and used as a generic object detector through a convolution neural network, using the sensory network’s video streams. The network’s performance was analysed to ensure that the network could carry out detection in real-time. A low-cost CMOS camera sensor network with a smartphone found an application, using Wi-Fi Direct, to create an intra-vehicle wireless network as a low-cost advanced driver-assistance system. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Research on Distributed Multi-Sensor Cooperative Scheduling Model Based on Partially Observable Markov Decision Process
Sensors 2022, 22(8), 3001; https://doi.org/10.3390/s22083001 - 14 Apr 2022
Cited by 1 | Viewed by 605
Abstract
In the context of distributed defense, multi-sensor networks are required to be able to carry out reasonable planning and scheduling to achieve the purpose of continuous, accurate and rapid target detection. In this paper, a multi-sensor cooperative scheduling model based on the partially [...] Read more.
In the context of distributed defense, multi-sensor networks are required to be able to carry out reasonable planning and scheduling to achieve the purpose of continuous, accurate and rapid target detection. In this paper, a multi-sensor cooperative scheduling model based on the partially observable Markov decision process is proposed. By studying the partially observable Markov decision process and the posterior Cramer–Rao lower bound, a multi-sensor cooperative scheduling model and optimization objective function were established. The improvement of the particle filter algorithm by the beetle swarm optimization algorithm was studied to improve the tracking accuracy of the particle filter. Finally, the improved elephant herding optimization algorithm was used as the solution algorithm of the scheduling scheme, which further improved the algorithm performance of the solution model. The simulation results showed that the model could solve the distributed multi-sensor cooperative scheduling problem well, had higher solution performance than other algorithms, and met the real-time requirements. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
A Subspace Pre-Learning Strategy to Break the Interpose PUF
Electronics 2022, 11(7), 1049; https://doi.org/10.3390/electronics11071049 - 27 Mar 2022
Viewed by 831
Abstract
Physical Unclonable Functions (PUFs) are promising security primitives for resource-constrained IoT devices. A critical aspect of PUF security research is to identify all potential security risks. This information about vulnerabilities is beneficial for both PUF developers and PUF-using application developers in terms of [...] Read more.
Physical Unclonable Functions (PUFs) are promising security primitives for resource-constrained IoT devices. A critical aspect of PUF security research is to identify all potential security risks. This information about vulnerabilities is beneficial for both PUF developers and PUF-using application developers in terms of designing new PUFs to mitigate existing risks and avoid vulnerable PUFs. Recently, a PUF structure called Interpose PUF (IPUF) was proposed, which claims to be resistant to reliability attacks and machine learning modeling attacks. Related studies on this secure PUF design have demonstrated that some IPUFs can still be broken, but large IPUFs may remain secure against all known modeling attacks. In addition, all these studies either focus on plain challenge–response pair attacks or require prior knowledge of IPUF architecture implementation. However, depending on the claim of attack resistance to reliability attacks, we can employ a different attack approach to break IPUFs. In this paper, we describe a subspace pre-learning-based attack method that can rapidly and accurately break the IPUFs that were treated as secure in the earlier study, revealing a vulnerability in IPUFs if the open interface conforms to the way challenge–response data are accessed by the subspace pre-learning-based attack method. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
A Data Aggregation Approach Exploiting Spatial and Temporal Correlation among Sensor Data in Wireless Sensor Networks
Electronics 2022, 11(7), 989; https://doi.org/10.3390/electronics11070989 - 23 Mar 2022
Cited by 4 | Viewed by 1142
Abstract
Wireless sensor networks (WSNs) have various applications which include zone surveillance, environmental monitoring, event tracking where the operation mode is long term. WSNs are characterized by low-powered and battery-operated sensor devices with a finite source of energy. Due to the dense deployment of [...] Read more.
Wireless sensor networks (WSNs) have various applications which include zone surveillance, environmental monitoring, event tracking where the operation mode is long term. WSNs are characterized by low-powered and battery-operated sensor devices with a finite source of energy. Due to the dense deployment of these devices practically it is impossible to replace the batteries. The finite source of energy should be utilized in a meaningful way to maximize the overall network lifetime. In the space domain, there is a high correlation among sensor surveillance constituting the large volume of the sensor network topology. Each consecutive observation constitutes the temporal correlation depending on the physical phenomenon nature of the sensor nodes. These spatio-temporal correlations can be efficiently utilized in order to enhance the maximum savings in energy uses. In this paper, we have proposed a Spatial and Temporal Correlation-based Data Redundancy Reduction (STCDRR) protocol which eliminates redundancy at the source level and aggregator level. The estimated performance score of proposed algorithms is approximately 7.2 when the score of existing algorithms such as the KAB (K-means algorithm based on the ANOVA model and Bartlett test) and ED (Euclidian distance) are 5.2, 0.5, respectively. It reflects that the STCDRR protocol can achieve a higher data compression rate, lower false-negative rate, lower false-positive rate. These results are valid for numeric data collected from a real data set. This experiment does not consider non-numeric values. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms
Electronics 2022, 11(6), 869; https://doi.org/10.3390/electronics11060869 - 09 Mar 2022
Cited by 4 | Viewed by 1157
Abstract
Clustering of sensor nodes is a prominent method applied to wireless sensor networks (WSNs). In a cluster-based WSN scenario, the sensor nodes are assembled to generate clusters. The sensor nodes also have limited battery power. Therefore, energy efficiency in WSNs is crucial. The [...] Read more.
Clustering of sensor nodes is a prominent method applied to wireless sensor networks (WSNs). In a cluster-based WSN scenario, the sensor nodes are assembled to generate clusters. The sensor nodes also have limited battery power. Therefore, energy efficiency in WSNs is crucial. The load on the sensor node and its distance from the base station (BS) are the significant factors of energy consumption. Therefore, load balancing according to the transmission distance is necessary for WSNs. In this paper, we propose a hybrid routing algorithm based on Naïve Bayes and improved particle swarm optimization algorithms (HRA-NP). The cluster heads (CHs) are selected according to the CH conditional probability, which is estimated by the Naïve Bayes classifier. After the selection of the CHs, the multi-hop routing algorithm is applied to the CHs. The best routing path from each CH to the BS is obtained from an improved particle swarm optimization (PSO) algorithm. Simulations were conducted on evaluation factors such as energy consumption, active sensor nodes per round, the sustainability of the network, and the standard deviation of a load on the sensor node. It was observed that HRA-NP outperforms comparable algorithms, namely DUCF, ECRRS, and FC-RBAT, based on the evaluation factors. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Missing and Corrupted Data Recovery in Wireless Sensor Networks Based on Weighted Robust Principal Component Analysis
Sensors 2022, 22(5), 1992; https://doi.org/10.3390/s22051992 - 03 Mar 2022
Cited by 2 | Viewed by 812
Abstract
Although wireless sensor networks (WSNs) have been widely used, the existence of data loss and corruption caused by poor network conditions, sensor bandwidth, and node failure during transmission greatly affects the credibility of monitoring data. To solve this problem, this paper proposes a [...] Read more.
Although wireless sensor networks (WSNs) have been widely used, the existence of data loss and corruption caused by poor network conditions, sensor bandwidth, and node failure during transmission greatly affects the credibility of monitoring data. To solve this problem, this paper proposes a weighted robust principal component analysis method to recover the corrupted and missing data in WSNs. By decomposing the original data into a low-rank normal data matrix and a sparse abnormal matrix, the proposed method can identify the abnormal data and avoid the influence of corruption on the reconstruction of normal data. In addition, the low-rankness is constrained by weighted nuclear norm minimization instead of the nuclear norm minimization to preserve the major data components and ensure credible reconstruction data. An alternating direction method of multipliers algorithm is further developed to solve the resultant optimization problem. Experimental results demonstrate that the proposed method outperforms many state-of-the-art methods in terms of recovery accuracy in real WSNs. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
A Correlation-Based Anomaly Detection Model for Wireless Body Area Networks Using Convolutional Long Short-Term Memory Neural Network
Sensors 2022, 22(5), 1951; https://doi.org/10.3390/s22051951 - 02 Mar 2022
Cited by 1 | Viewed by 1046
Abstract
As the Internet of Healthcare Things (IoHT) concept emerges today, Wireless Body Area Networks (WBAN) constitute one of the most prominent technologies for improving healthcare services. WBANs are made up of tiny devices that can effectively enhance patient quality of life by collecting [...] Read more.
As the Internet of Healthcare Things (IoHT) concept emerges today, Wireless Body Area Networks (WBAN) constitute one of the most prominent technologies for improving healthcare services. WBANs are made up of tiny devices that can effectively enhance patient quality of life by collecting and monitoring physiological data and sending it to healthcare givers to assess the criticality of a patient and act accordingly. The collected data must be reliable and correct, and represent the real context to facilitate right and prompt decisions by healthcare personnel. Anomaly detection becomes a field of interest to ensure the reliability of collected data by detecting malicious data patterns that result due to various reasons such as sensor faults, error readings and possible malicious activities. Various anomaly detection solutions have been proposed for WBAN. However, existing detection approaches, which are mostly based on statistical and machine learning techniques, become ineffective in dealing with big data streams and novel context anomalous patterns in WBAN. Therefore, this paper proposed a model that employs the correlations that exist in the different physiological data attributes with the ability of the hybrid Convolutional Long Short-Term Memory (ConvLSTM) techniques to detect both simple point anomalies as well as contextual anomalies in the big data stream of WBAN. Experimental evaluations revealed that an average of 98% of F1-measure and 99% accuracy were reported by the proposed model on different subjects of the datasets compared to 64% achieved by both CNN and LSTM separately. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Combining 10 Matrix Pressure Sensor to Read Human Body’s Pressure in Sleeping Position in Relation with Decubitus Patients
J. Sens. Actuator Netw. 2022, 11(1), 16; https://doi.org/10.3390/jsan11010016 - 25 Feb 2022
Viewed by 1761
Abstract
This work uses piezoresistive matrix pressure sensors to map the human body’s pressure profile in a sleeping position. This study aims to detect the area with the highest pressure, to visualize the pressure profile into a heatmap, and to reduce decubitus by alerting [...] Read more.
This work uses piezoresistive matrix pressure sensors to map the human body’s pressure profile in a sleeping position. This study aims to detect the area with the highest pressure, to visualize the pressure profile into a heatmap, and to reduce decubitus by alerting the subject to changes in position. This research combines ten matrix pressure sensors to read a larger area. This work uses a Raspberry Pi 4 Model B with 8 GB memory as the data processor, and every sensor sheet uses ATMEGA 2560 as the sensor controller for data acquisition. Sensor calibration is necessary because each output must have the same value for the same weight value; the accuracy between different sensors is around 95%. After the calibration process, the output data must be smoothed to make visual representations more distinguishable. The areas with the highest pressure are the heel, tailbone, back, and head. When the subject’s weight increases, pressure on the tailbone and back increases, but that on the heel and head does not. The results of this research can be used to monitor people’s sleeping positions so that they can reduce the risk of decubitus. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Communication
Novel Cooperative Automatic Modulation Classification Using Vectorized Soft Decision Fusion for Wireless Sensor Networks
Sensors 2022, 22(5), 1797; https://doi.org/10.3390/s22051797 - 24 Feb 2022
Cited by 2 | Viewed by 734
Abstract
Cooperative automatic modulation classification (CAMC) using a swarm of sensors is intriguing nowadays as it would be much more robust than the conventional single-sensing-node automatic modulation classification (AMC) method. We propose a novel robust CAMC approach using vectorized soft decision fusion in this [...] Read more.
Cooperative automatic modulation classification (CAMC) using a swarm of sensors is intriguing nowadays as it would be much more robust than the conventional single-sensing-node automatic modulation classification (AMC) method. We propose a novel robust CAMC approach using vectorized soft decision fusion in this work. In each sensing node, the local Hamming distances between the graph features acquired from the unknown target signal and the training modulation candidate signals are calculated and transmitted to the fusion center (FC). Then, the global CAMC decision is made by the indirect vote which is translated from each sensing node’s Hamming-distance sequence. The simulation results demonstrate that, when the signal-to-noise ratio (SNR) was given by η0dB, our proposed new CAMC scheme’s correct classification probability Pcc could reach up close to 100%. On the other hand, our proposed new CAMC scheme could significantly outperform the single-node graph-based AMC technique and the existing decision-level CAMC method in terms of recognition accuracy, especially in the low-SNR regime. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Simple and Robust Log-Likelihood Ratio Calculation of Coded MPSK Signals in Wireless Sensor Networks for Healthcare
Appl. Sci. 2022, 12(5), 2330; https://doi.org/10.3390/app12052330 - 23 Feb 2022
Viewed by 565
Abstract
The simple and robust log-likelihood ratio (LLR) computation of coded Multiple Phase Shift Keying (MPSK) signals in Wireless Sensor Networks (WSNs) is considered under both phase noncoherent and Rayleigh fading channels for healthcare applications. We first simplify the optimal LLR for phase noncoherent [...] Read more.
The simple and robust log-likelihood ratio (LLR) computation of coded Multiple Phase Shift Keying (MPSK) signals in Wireless Sensor Networks (WSNs) is considered under both phase noncoherent and Rayleigh fading channels for healthcare applications. We first simplify the optimal LLR for phase noncoherent channel, the estimation of the instantaneous channel state information (CSI) for both the fading amplitude and the additive white Gaussian noise (AWGN) is successfully avoided, and the complexity-intensive process for zero-order Bessel function of the first kind is also perfectly eliminated. Furthermore, we also develop the simplified LLR under Rayleigh fading channel. Correspondingly, the variance estimation for both AWGN and the statistical characteristic of the fading amplitude is no longer required, and the complicated process for implementation of the exponential function is also successfully avoided. Compared to the calculation of optimal LLR with full complexity, the proposed method is implementation-friendly, which is practically desired for energy-limited WSNs. The simulations are developed in the context of low-density parity-check (LDPC) codes, and the corresponding results show that the detection performance is extremely close to that of the full-complexity LLR metrics. That is, the performance degradation is efficiently prevented, whereas complexity reduction is also successfully achieved. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Area-Efficient Integrated Current-Reuse Feedback Amplifier for Wake-Up Receivers in Wireless Sensor Network Applications
Sensors 2022, 22(4), 1662; https://doi.org/10.3390/s22041662 - 21 Feb 2022
Viewed by 813
Abstract
Wireless sensor network (WSN) applications are under extensive research and development due to the need to interconnect devices with each other. To reduce latency while keeping very low power consumption, the implementation of a wake-up receiver (WuR) is of particular interest. In WuR [...] Read more.
Wireless sensor network (WSN) applications are under extensive research and development due to the need to interconnect devices with each other. To reduce latency while keeping very low power consumption, the implementation of a wake-up receiver (WuR) is of particular interest. In WuR implementations, meeting high performance metrics is a design challenge, and the obtention of high-sensitivity, high data rate, low-power-consumption WuRs is not a straightforward procedure. The focus of our proposals is centered on power consumption and area reduction to provide high integrability and maintain a low cost-per-node, while we simultaneously improve circuit sensitivity. Firstly, we present a two-stage design based on a feedback technique and improve the area use, power consumption and sensitivity of the circuit by adding a current-reuse approach. The first solution is composed of a feedback amplifier, two op-amps plus a low-pass filter. The circuit achieves a sensitivity of –63.2 dBm with a power consumption of 6.77 µA and an area as low as 398 × 266 µm2. With the current-reuse feedback amplifier, the power consumption is halved in the second circuit (resulting in 3.63 µA), and the resulting circuit area is as low as 262 × 262 µm2. Thanks to the nature of the circuit, the sensitivity is improved to –75 dBm. This latter proposal is particularly suitable in applications where a fully integrated WuR is desired, providing a reasonable sensitivity with a low power consumption and a very low die footprint, therefore facilitating integration with other components of the WSN node. A thorough discussion of the most relevant state-of-the-art solutions is presented, too, and the two developed solutions are compared to the most relevant contributions available in the literature. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
All-Directional DOA Estimation for Ultra-Wideband Regular Tetrahedral Array Using Wrapped PDoA
Sensors 2022, 22(4), 1532; https://doi.org/10.3390/s22041532 - 16 Feb 2022
Viewed by 822
Abstract
In this paper, we proposed a Regular Tetrahedral Array (RTA) to cope with various types of sensors expected in Ultra-Wideband (UWB) localization requiring all-directional detection capability and high accuracy, such as indoor Internet-of-Things (IoT) devices at diverse locations, UAVs performing aerial navigation, collision [...] Read more.
In this paper, we proposed a Regular Tetrahedral Array (RTA) to cope with various types of sensors expected in Ultra-Wideband (UWB) localization requiring all-directional detection capability and high accuracy, such as indoor Internet-of-Things (IoT) devices at diverse locations, UAVs performing aerial navigation, collision avoidance and takeoff/landing guidance. The RTA is deployed with four synchronized Ultra-Wideband (UWB) transceivers on its vertexes and configured with arbitrary aperture. An all-directional DOA estimation algorithm using combined TDoA and wrapped PDoA was conducted. The 3D array RTA was decomposed into four planar subarrays solved as phased Uniform Circular Array (UCA) respectively. A new cost function based on geometric identical and variable neighborhood search strategy using TDoA information was proposed for ambiguity resolution. The results of simulation and numerical experiments demonstrated excellent performance of the proposed RTA and corresponding algorithm. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Noise Immunity-Enhanced Capacitance Readout Circuit for Human Interaction Detection in Human Body Communication Systems
Electronics 2022, 11(4), 577; https://doi.org/10.3390/electronics11040577 - 14 Feb 2022
Viewed by 731
Abstract
Recent healthcare systems based on human body communication (HBC) require human interaction sensors. Due to the conductive properties of the human body, capacitive sensors are most widely known and are applied to many electronic gadgets for communication. Capacitance fluctuations due to the fact [...] Read more.
Recent healthcare systems based on human body communication (HBC) require human interaction sensors. Due to the conductive properties of the human body, capacitive sensors are most widely known and are applied to many electronic gadgets for communication. Capacitance fluctuations due to the fact of human interaction are typically converted to voltage levels using some analog circuits, and then analog-to-digital converters (ADCs) are used to convert analog voltages into digital codes for further processing. However, signals detected by human touch naturally contain large noise, and an active analog filter that consumes a lot of power is required. In addition, the inclusion of ADCs causes the system to use a large area and amount of power. The proposed structure adopts a digital-based moving average filter (MAF) that can effectively operate as a low-pass filter (LPF) instead of a large-area and high-power consumption analog filter. In addition, the proposed ∆C detection algorithm can distinguish between human interaction and object interaction. As a result, two individual digital signals of touch/release and movement can be generated, and the type and strength of the touch can be effectively expressed without the help of an ADC. The prototype chip of the proposed capacitive sensing circuit was fabricated with commercial 65 nm CMOS process technology, and its functionality was fully verified through testing and measurement. The prototype core occupies an active area of 0.0067 mm2, consumes 7.5 uW of power, and has a conversion time of 105 ms. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Deep Graph Reinforcement Learning Based Intelligent Traffic Routing Control for Software-Defined Wireless Sensor Networks
Appl. Sci. 2022, 12(4), 1951; https://doi.org/10.3390/app12041951 - 13 Feb 2022
Cited by 1 | Viewed by 932
Abstract
Software-defined wireless sensor networks (SDWSN), where the data and control planes are decoupled, are more suited to handling big sensor data and effectively monitoring dynamic environments and events. To overcome the limitations of using static routing tables under high traffic intensity, such as [...] Read more.
Software-defined wireless sensor networks (SDWSN), where the data and control planes are decoupled, are more suited to handling big sensor data and effectively monitoring dynamic environments and events. To overcome the limitations of using static routing tables under high traffic intensity, such as network congestion, high packet loss rate, low throughput, etc., it is critical to design intelligent traffic routing control for the SDWSNs. In this paper we propose a deep graph reinforcement learning (DGRL) model-based intelligent traffic control scheme for SDWSNs, which combines graph convolution with deterministic policy gradient. The model fits well for the task of intelligent routing control for the SDWSN, as the process of data forwarding can be regarded as the sampling of continuous action space and the traffic data has strong graph features. The intelligent control policies are made by the SDWSN controller and implemented at the sensor nodes to optimize the data forwarding process. Simulation experiments performed on the Omnet++ platform show that, compared with the existing traffic routing algorithms for SDWSNs, the proposed intelligent routing control method can effectively reduce packet transmission delay, increase packet delivery ratio, and reduce the probability of network congestion. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
SPMOO: A Multi-Objective Offloading Algorithm for Dependent Tasks in IoT Cloud-Edge-End Collaboration
Information 2022, 13(2), 75; https://doi.org/10.3390/info13020075 - 05 Feb 2022
Cited by 1 | Viewed by 1442
Abstract
With the rapid development of the internet of things, there are more and more end devices, such as wearable devices, USVs and intelligent automobiles, connected to the internet. These devices tend to require large amounts of computing resources with stringent latency requirements, which [...] Read more.
With the rapid development of the internet of things, there are more and more end devices, such as wearable devices, USVs and intelligent automobiles, connected to the internet. These devices tend to require large amounts of computing resources with stringent latency requirements, which inevitably increases the burden on edge server nodes. Therefore, in order to alleviate the problem that the computing capacity of edge server nodes is limited and cannot meet the computing service requirements of a large number of end devices in the internet of things scenario, we combined the characteristics of rich computing resources of cloud servers and low transmission delay of edge servers to build a hybrid computing task-offloading architecture of cloud-edge-end collaboration. Then, we study offloading based on this architecture for complex dependent tasks generated on end devices. We introduce a two-dimensional offloading decision factor to model latency and energy consumption, and formalize the model as a multi-objective optimization problem with the optimization objective of minimizing the average latency and average energy consumption of the task’s computation offloading. Based on this, we propose a multi-objective offloading (SPMOO) algorithm based on an improved strength Pareto evolutionary algorithm (SPEA2) for solving the problem. A large number of experimental results show that the algorithm proposed in this paper has good performance. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
Using Adaptive Sensors for Optimised Target Coverage in Wireless Sensor Networks
Sensors 2022, 22(3), 1083; https://doi.org/10.3390/s22031083 - 30 Jan 2022
Cited by 7 | Viewed by 2024
Abstract
Innovation in wireless communications and microtechnology has progressed day by day, and this has resulted in the creation of wireless sensor networks. This technology is utilised in a variety of settings, including battlefield surveillance, home security, and healthcare monitoring, among others. However, since [...] Read more.
Innovation in wireless communications and microtechnology has progressed day by day, and this has resulted in the creation of wireless sensor networks. This technology is utilised in a variety of settings, including battlefield surveillance, home security, and healthcare monitoring, among others. However, since tiny batteries with very little power are used, this technology has power and target monitoring issues. With the development of various architectures and algorithms, considerable research has been done to address these problems. The adaptive learning automata algorithm (ALAA) is a scheduling machine learning method that is utilised in this study. It offers a time-saving scheduling method. As a result, each sensor node in the network has been outfitted with learning automata, allowing them to choose their appropriate state at any given moment. The sensor is in one of two states: active or sleep. Several experiments were conducted to get the findings of the suggested method. Different parameters are utilised in this experiment to verify the consistency of the method for scheduling the sensor node so that it can cover all of the targets while using less power. The experimental findings indicate that the proposed method is an effective approach to schedule sensor nodes to monitor all targets while using less electricity. Finally, we have benchmarked our technique against the LADSC scheduling algorithm. All of the experimental data collected thus far demonstrate that the suggested method has justified the problem description and achieved the project’s aim. Thus, while constructing an actual sensor network, our suggested algorithm may be utilised as a useful technique for scheduling sensor nodes. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Review
Formal Modeling and Improvement in the Random Path Routing Network Scheme Using Colored Petri Nets
Appl. Sci. 2022, 12(3), 1426; https://doi.org/10.3390/app12031426 - 28 Jan 2022
Cited by 1 | Viewed by 1173
Abstract
Wireless sensor networks (WSNs) have been applied in networking devices, and a new problem has emerged called source-location privacy (SLP) in critical security systems. In wireless sensor networks, hiding the location of the source node from the hackers is known as SLP. The [...] Read more.
Wireless sensor networks (WSNs) have been applied in networking devices, and a new problem has emerged called source-location privacy (SLP) in critical security systems. In wireless sensor networks, hiding the location of the source node from the hackers is known as SLP. The WSNs have limited battery capacity and low computational ability. Many state-of-the-art protocols have been proposed to address the SLP problems and other problems such as limited battery capacity and low computational power. One of the popular protocols is random path routing (RPR), and in random path routing, the system keeps sending the message randomly along all the possible paths from a source node to a sink node irrespective of the path’s distance. The problem arises when the system keeps sending a message via the longest route, resulting because of high battery usage and computational costs. This research paper presents a novel networking model referred to as calculated random path routing (CRPR). CRPR first calculates the top three shortest paths, and then randomly sends a token to any of the top three shortest calculated paths, ensuring the optimal tradeoff between computational cost and SLP. The proposed methodology includes the formal modeling of the CRPR in Colored Petri Nets. We have validated and verified the CRPR, and the results depict the optimal tradeoff. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
A Method of Optimizing Characteristic Impedance Compensation Using Cut-Outs in High-Density PCB Designs
Sensors 2022, 22(3), 964; https://doi.org/10.3390/s22030964 - 26 Jan 2022
Cited by 1 | Viewed by 1417
Abstract
The modern era of technology contains a myriad of high-speed standards and proprietary serial digital protocols, which evolve alongside the microwave and RF realm. The increasing data rate push the requirements for hardware design, including modern printed circuit boards (PCB). One of these [...] Read more.
The modern era of technology contains a myriad of high-speed standards and proprietary serial digital protocols, which evolve alongside the microwave and RF realm. The increasing data rate push the requirements for hardware design, including modern printed circuit boards (PCB). One of these requirements for modern high-speed PCB interfaces are a homogenous track impedance all the way from the source to the load. Even though some high-speed interfaces don’t require any external components embedded into the interconnects, there are others which require either passive or active components—or both. Usually, component package land-pads are of fixed size, thus, if not addressed, they create discontinuities and degrade the transmitted signal. To solve this problem, impedance compensation techniques such as reference plane cut-out are employed for multiple case studies covering this topic. This paper presents an original method of finding the optimal cut-out size for the maximum characteristic impedance compensation in high-density multilayer PCB designs, which has been verified via theoretical estimation, computer simulation, and practical measurement results. Track-to-discontinuity ratios of 1:1.75, 1:2.5, and 1:5.0 were selected in order to resemble most practical design scenarios on a 6-layer standard thickness PCB. The measurements and simulations revealed that the compensated impedance saturation occurs at (150–250%) cut-out widths for a 50 Ω microstrip. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
AntTrust: An Ant-Inspired Trust Management System for Peer-to-Peer Networks
Sensors 2022, 22(2), 533; https://doi.org/10.3390/s22020533 - 11 Jan 2022
Cited by 1 | Viewed by 715
Abstract
In P2P networks, self-organizing anonymous peers share different resources without a central entity controlling their interactions. Peers can join and leave the network at any time, which opens the door to malicious attacks that can damage the network. Therefore, trust management systems that [...] Read more.
In P2P networks, self-organizing anonymous peers share different resources without a central entity controlling their interactions. Peers can join and leave the network at any time, which opens the door to malicious attacks that can damage the network. Therefore, trust management systems that can ensure trustworthy interactions between peers are gaining prominence. This paper proposes AntTrust, a trust management system inspired by the ant colony. Unlike other ant-inspired algorithms, which usually adopt a problem-independent approach, AntTrust follows a problem-dependent (problem-specific) heuristic to find a trustworthy peer in a reasonable time. It locates a trustworthy file provider based on four consecutive trust factors: current trust, recommendation, feedback, and collective trust. Three rival trust management paradigms, namely, EigenTrust, Trust Network Analysis with Subjective Logic (TNA-SL), and Trust Ant Colony System (TACS), were tested to benchmark the performance of AntTrust. The experimental results demonstrate that AntTrust is capable of providing a higher and more stable success rate at a low running time regardless of the percentage of malicious peers in the network. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
TSCH Multiflow Scheduling with QoS Guarantees: A Comparison of SDN with Common Schedulers
Appl. Sci. 2022, 12(1), 119; https://doi.org/10.3390/app12010119 - 23 Dec 2021
Viewed by 1344
Abstract
Industrial Wireless Sensor Networks (IWSN) are becoming increasingly popular in production environments due to their ease of deployment, low cost and energy efficiency. However, the complexity and accuracy demanded by these environments requires that IWSN implement quality of service mechanisms that allow them [...] Read more.
Industrial Wireless Sensor Networks (IWSN) are becoming increasingly popular in production environments due to their ease of deployment, low cost and energy efficiency. However, the complexity and accuracy demanded by these environments requires that IWSN implement quality of service mechanisms that allow them to operate with high determinism. For this reason, the IEEE 802.15.4e standard incorporates the Time Slotted Channel Hopping (TSCH) protocol which reduces interference and increases the reliability of transmissions. This standard does not specify how time resources are allocated in TSCH scheduling, leading to multiple scheduling solutions. Schedulers can be classified as autonomous, distributed and centralised. The first two have prevailed over the centralised ones because they do not require high signalling, along with the advantages of ease of deployment and high performance. However, the increased QoS requirements and the diversity of traffic flows that circulate through the network in today’s Industry 4.0 environment require strict, dynamic control to guarantee parameters such as delay, packet loss and deadline, independently for each flow. That cannot always be achieved with distributed or autonomous schedulers. For this reason, it is necessary to use centralised protocols with a disruptive approach, such as Software Defined Networks (SDN). In these, not only is the control of the MAC layer centralised, but all the decisions of the nodes that make up the network are configured by the controller based on a global vision of the topology and resources, which allows optimal decisions to be made. In this work, a comparative analysis is made through simulation and a testbed of the different schedulers to demonstrate the benefits of a fully centralized approach such as SDN. The results obtained show that with SDN it is possible to simplify the management of multiple flows, without the problems of centralised schedulers. SDN maintains the Packet Delivery Ratio (PDR) levels of other distributed solutions, but in addition, it achieves greater determinism with bounded end-to-end delays and Deadline Satisfaction Ratio (DSR) at the cost of increased power consumption. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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Article
The Role of Genetic Algorithm Selection Operators in Extending WSN Stability Period: A Comparative Study
Electronics 2022, 11(1), 28; https://doi.org/10.3390/electronics11010028 - 22 Dec 2021
Cited by 2 | Viewed by 1330
Abstract
A genetic algorithm (GA) contains a number of genetic operators that can be tweaked to improve the performance of specific implementations. Parent selection, crossover, and mutation are examples of these operators. One of the most important operations in GA is selection. The performance [...] Read more.
A genetic algorithm (GA) contains a number of genetic operators that can be tweaked to improve the performance of specific implementations. Parent selection, crossover, and mutation are examples of these operators. One of the most important operations in GA is selection. The performance of GA in addressing the single-objective wireless sensor network stability period extension problem using various parent selection methods is evaluated and compared. In this paper, six GA selection operators are used: roulette wheel, linear rank, exponential rank, stochastic universal sampling, tournament, and truncation. According to the simulation results, the truncation selection operator is the most efficient operator in terms of extending the network stability period and improving reliability. The truncation operator outperforms other selection operators, most notably the well-known roulette wheel operator, by increasing the stability period by 25.8% and data throughput by 26.86%. Furthermore, the truncation selection operator outperforms other selection operators in terms of the network residual energy after each protocol round. Full article
(This article belongs to the Topic Wireless Sensor Networks)
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