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Feature Papers in the Sensor Networks Section 2022

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

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 30226

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Prof. Dr. Yuh-Shyan Chen

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Department of Computer Science and Information Engineering, National Taipei University, No. 151, University Rd., San Shia District, New Taipei City 23741, Taiwan
Interests: wireless communication and mobile computing; The Next-Generation Mobile Network and System
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Iain Collings

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Guest Editor

School of Engineering, Macquarie University, Sydney, NSW 2113, Australia
Interests: signal processing signal processing for communication cellular communication information theory wireless communications radio propagation channel estimation communication engineering

Prof. Dr. Paolo Visconti

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Guest Editor

Departament of Innovation Engineering, University of Salento, 73100 Lecce, Italy
Interests: design and testing of IoT-based electronic systems; smart remote control of facilities; electronic systems for automation and automotive; energy harvesting systems for sensors nodes; wearable devices for health monitoring; new materials and advanced sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce that the Section “Sensor Networks” is now compiling a collection of papers submitted by the Section’s Editorial Board Members (EBMs) and outstanding scholars in this research field. We welcome contributions as well as recommendations from EBMs.

We expect original papers and review articles showing state-of-the-art, theoretical, and applicative advances, new experimental discoveries, and novel technological improvements regarding Sensor Networks. We expect these papers to be widely read and highly influential within the field. All papers in this Special Issue will be collected into a printed edition book after the deadline, and be well promoted.

We would also like to take this opportunity to call on more excellent scholars to join the Sensor Networks Section so that we can work together to further develop this exciting field of research.

Prof. Dr. Yuh-Shyan Chen
Prof. Dr. Iain Collings
Prof. Dr. Paolo Visconti
Guest Editors

Manuscript Submission Information

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

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

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Published Papers (9 papers)

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15 pages, 16244 KiB

Open AccessArticle

Aligned Matching: Improving Small Object Detection in SSD

by Seok-Hoon Kang and Joon-Sang Park

Sensors 2023, 23(5), 2589; https://doi.org/10.3390/s23052589 - 26 Feb 2023

Cited by 11 | Viewed by 3350

Abstract

Although detecting small objects is critical in various applications, neural network models designed and trained for generic object detection struggle to do so with precision. For example, the popular Single Shot MultiBox Detector (SSD) tends to perform poorly for small objects, and balancing the performance of SSD across different sized objects remains challenging. In this study, we argue that the current IoU-based matching strategy used in SSD reduces the training efficiency for small objects due to improper matches between default boxes and ground truth objects. To address this issue and improve the performance of SSD in detecting small objects, we propose a new matching strategy called aligned matching that considers aspect ratios and center-point distance in addition to IoU. The results of experiments on the TT100K and Pascal VOC datasets show that SSD with aligned matching detected small objects significantly better without sacrificing performance on large objects or requiring extra parameters. Full article

(This article belongs to the Special Issue Feature Papers in the Sensor Networks Section 2022)

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24 pages, 36209 KiB

Open AccessArticle

MmWave Physical Layer Network Modeling and Planning for Fixed Wireless Access Applications

by Brecht De Beelde, Mike Vantorre, German Castellanos, Mario Pickavet and Wout Joseph

Sensors 2023, 23(4), 2280; https://doi.org/10.3390/s23042280 - 17 Feb 2023

Cited by 6 | Viewed by 3008

Abstract

The large bandwidths that are available at millimeter-wave frequencies enable fixed wireless access (FWA) applications, in which fixed point-to-point wireless links are used to provide internet connectivity. In FWA networks, a wireless mesh is created and data are routed from the customer premises equipment (CPE) towards the point of presence (POP), which is the interface with the wired internet infrastructure. The performance of the wireless links depends on the radio propagation characteristics, as well as the wireless technology that is used. The radio propagation characteristics depend on the environment and on the considered frequency. In this work, we analyzed the network characteristics of FWA networks using radio propagation models for different wireless technologies using millimeter-wave (mmWave) frequencies of 28 GHz, 60 GHz, and 140 GHz. Different scenarios and environments were considered, and the influence of rain, vegetation, and the number of subscribers was investigated. A network planning algorithm is presented that defines a route for each CPE towards the POP based on a predefined location of customer devices and considering the available capacity of the wireless links. Rain does not have a considerable effect on the system capacity. Even though the higher frequencies exhibit a larger path loss, resulting in a lower power of the received signal, the larger bandwidths enable a higher channel capacity. Full article

(This article belongs to the Special Issue Feature Papers in the Sensor Networks Section 2022)

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26 pages, 10442 KiB

Open AccessArticle

Evaluating 60 GHz FWA Deployments for Urban and Rural Environments in Belgium

by German Castellanos, Brecht De Beelde, David Plets, Luc Martens, Wout Joseph and Margot Deruyck

Sensors 2023, 23(3), 1056; https://doi.org/10.3390/s23031056 - 17 Jan 2023

Cited by 3 | Viewed by 3371

Abstract

Fixed wireless access (FWA) provides a solution to compete with fiber deployment while offering reduced costs by using the mmWave bands, including the unlicensed 60 GHz one. This paper evaluates the deployment of FWA networks in the 60 GHz band in realistic urban and rural environment in Belgium. We developed a network planning tool that includes novel backhaul based on the IEEE 802.11ay standard with multi-objective capabilities to maximise the user coverage, providing at least 1 Gbps of bit rate while minimising the required network infrastructure. We evaluate diverse serving node locations, called edge nodes (EN), and the impact of environmental factors such as rain and vegetation on the network design. Extensive simulation results show that defining a proper EN’s location is essential to achieve viable user coverage higher than 95%, particularly in urban scenarios where street canyons affect propagation. Rural scenarios require nearly 75 ENs per km

^{2}

while urban scenarios require four times (300 ENs per km

^{2}

) this infrastructure. Finally, vegetation can reduce the coverage by 3% or increment infrastructure up to 7%, while heavy rain can reduce coverage by 5% or increment infrastructure by 15%, depending on the node deployment strategy implemented. Full article

(This article belongs to the Special Issue Feature Papers in the Sensor Networks Section 2022)

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40 pages, 15320 KiB

Open AccessArticle

Multi-Feature Transformer-Based Learning for Continuous Human Motion Recognition with High Similarity Using mmWave FMCW Radar

by Yuh-Shyan Chen, Kuang-Hung Cheng, You-An Xu and Tong-Ying Juang

Sensors 2022, 22(21), 8409; https://doi.org/10.3390/s22218409 - 1 Nov 2022

Cited by 6 | Viewed by 3031

Abstract

Doppler-radar-based continuous human motion recognition recently has attracted extensive attention, which is a favorable choice for privacy and personal security. Existing results of continuous human motion recognition (CHMR) using mmWave FMCW Radar are not considered the continuous human motion with the high similarity problem. In this paper, we proposed a new CHMR algorithm with the consideration of the high similarity (HS) problem, called as CHMR-HS, by using the modified Transformer-based learning model. As far as we know, this is the first result in the literature to investigate the continuous HMR with the high similarity. To obtain the clear FMCW radar images, the background and target signals of the detected human are separated through the background denoising and the target extraction algorithms. To investigate the effects of the spectral-temporal multi-features with different dimensions, Doppler, range, and angle signatures are extracted as the 2D features and range-Doppler-time and range-angle-time signatures are extracted as the 3D features. The 2D/3D features are trained into the adjusted Transformer-encoder model to distinguish the difference of the high-similarity human motions. The conventional Transformer-decoder model is also re-designed to be Transformer-sequential-decoder model such that Transformer-sequential-decoder model can successfully recognize the continuous human motions with the high similarity. The experimental results show that the accuracy of our proposed CHMR-HS scheme are 95.2% and 94.5% if using 3D and 2D features, the simulation results also illustrates that our CHMR-HS scheme has advantages over existing CHMR schemes. Full article

(This article belongs to the Special Issue Feature Papers in the Sensor Networks Section 2022)

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21 pages, 1898 KiB

Open AccessArticle

Reinforcement Learning-Aided Edge Intelligence Framework for Delay-Sensitive Industrial Applications

by Muhammad Zubair Islam, Shahzad, Rashid Ali, Amir Haider and Hyung Seok Kim

Sensors 2022, 22(20), 8001; https://doi.org/10.3390/s22208001 - 20 Oct 2022

Cited by 4 | Viewed by 2508

Abstract

With the advancement in next-generation communication technologies, the so-called Tactile Internet is getting more attention due to its smart applications, such as haptic-enabled teleoperation systems. The stringent requirements such as delay, jitter, and packet loss of these delay-sensitive and loss-intolerant applications make it more challenging to ensure the Quality of Service (QoS) and Quality of Experience (QoE). In this regard, different haptic codec and control schemes were proposed for QoS and QoE provisioning in the Tactile Internet. However, they maximize the QoE while degrading the system’s stability under varying delays and high packet rates. In this paper, we present a reinforcement learning-based Intelligent Tactile Edge (ITE) framework to ensure both transparency and stability of teleoperation systems with high packet rates and variable time delay communication networks. The proposed ITE first estimates the network challenges, including communication delay, jitter, and packet loss, and then utilizes a Q-learning algorithm to select the optimal haptic codec scheme to reduce network load. The proposed framework aims to explore the optimal relationship between QoS and QoE parameters and make the tradeoff between stability and transparency during teleoperations. The simulation result indicates that the proposed strategy chooses the optimal scheme under different network impairments corresponding to the congestion level in the communication network while improving the QoS and maximizing the QoE. The end-to-end performance of throughput (1.5 Mbps) and average RTT (70 ms) during haptic communication is achieved with a learning rate and discounted factor value of 0.5 and 0.8, respectively. The results indicate that the communication system can successfully achieve the QoS and QoE requirements by employing the proposed ITE framework. Full article

(This article belongs to the Special Issue Feature Papers in the Sensor Networks Section 2022)

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33 pages, 709 KiB

Open AccessArticle

An Infrastructure for Enabling Dynamic Fault Tolerance in Highly-Reliable Adaptive Distributed Embedded Systems Based on Switched Ethernet

by Alberto Ballesteros, Manuel Barranco, Julián Proenza, Luís Almeida, Francisco Pozo and Pere Palmer-Rodríguez

Sensors 2022, 22(18), 7099; https://doi.org/10.3390/s22187099 - 19 Sep 2022

Cited by 7 | Viewed by 2516

Abstract

Distributed Embedded Systems (DESs) carrying out critical tasks must be highly reliable and hard in real-time. Moreover, to operate in dynamic operational contexts in an effective and efficient manner, they must also be adaptive. Adaptivity is particularly interesting from a dependability perspective, as it can be used to develop dynamic fault tolerance mechanisms, which, in combination with static ones, make it possible to provide better and more efficient fault tolerance. However, constructing a DES with such complexity presents many challenges. This is because all the mechanisms that support fault tolerance, real-time, and adaptivity must be designed to operate in a coordinated manner. This paper presents the Dynamic Fault Tolerance for Flexible Time-Triggered Ethernet (DFT4FTT), a self-reconfigurable infrastructure for implementing highly reliable adaptive DES. Here, we describe the design of its hardware and software architecture and the main set of mechanisms, with a focus on fault tolerance. Full article

(This article belongs to the Special Issue Feature Papers in the Sensor Networks Section 2022)

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15 pages, 7498 KiB

Open AccessArticle

Enabling Real-Time Quality-of-Service and Fine-Grained Aggregation for Wireless TSN

by Litianyi Zhang, Yifan Gu, Rui Wang, Kan Yu, Zhibo Pang, Yonghui Li and Branka Vucetic

Sensors 2022, 22(10), 3901; https://doi.org/10.3390/s22103901 - 20 May 2022

Cited by 6 | Viewed by 2470

Abstract

Wireless Time-Sensitive Networking (WTSN) has emerged as a promising technology for Industrial Internet of Things (IIoT) applications. To meet the latency requirements of WTSN, wireless local area network (WLAN) such as IEEE 802.11 protocol with the time division multiple access (TDMA) mechanism is shown to be a practical solution. In this paper, we propose the RT-WiFiQA protocol with two novel schemes to improve the latency and reliability performance: real-time quality of service (RT-QoS) and fine-grained aggregation (FGA) for TDMA-based 802.11 systems. The RT-QoS is designed to guarantee the quality-of-service requirements of different traffic and to support the FGA mechanism. The FGA mechanism aggregates frames for different stations to reduce the physical layer transmission overhead. The trade-off between the reliability and FGA packet size is analyzed with numerical results. Specifically, we derive a critical threshold such that the FGA can achieve higher reliability when the aggregated packet size is smaller than the critical threshold. Otherwise, the non-aggregation scheme outperforms the FGA scheme. Extensive experiments are conducted on the commercial off-the-shelf 802.11 interface. The experiment results show that compared with the existing TDMA-based 802.11 system, the developed RT-WiFiQA protocol can achieve deterministic bounded real-time latency and greatly improves the reliability performance. Full article

(This article belongs to the Special Issue Feature Papers in the Sensor Networks Section 2022)

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24 pages, 1214 KiB

Open AccessArticle

Persistent Periodic Uplink Scheduling Algorithm for Massive NB-IoT Devices

by Tin-Yu Wu, Ren-Hung Hwang, Abhishek Vyas, Chia-Yiu Lin and Chi-Ruei Huang

Sensors 2022, 22(8), 2875; https://doi.org/10.3390/s22082875 - 8 Apr 2022

Cited by 3 | Viewed by 3234

Abstract

Narrowband Internet of Things (NB-IoT) is one of the low-power wide-area network (LPWAN) technologies that aim to support enormous connections, featuring wide-area coverage, low power consumption, and low costs. NB-IoT could serve a massive number of IoT devices, but with very limited radio resources. Therefore, how to enable a massive number of IoT devices to transmit messages periodically, and with low latency, according to transmission requirements, has become the most crucial issue of NB-IoT. Moreover, IoT devices are designed to minimize power consumption so that the device battery can last for a long time. Similarly, the NB-IoT system must configure different power-saving mechanisms for different types of devices to prolong their battery lives. In this study, we propose a persistent periodic uplink scheduling algorithm (PPUSA) to assist a plethora of Internet of Things (IoT) devices in reporting their sensing data based on their sensing characteristics. PPUSA explicitly considers the power-saving mode and connection suspend/resume procedures to reduce the IoT device’s power consumption and processing overhead. PPUSA allocates uplink resource units to IoT devices systematically so that it can support the periodic–uplink transmission of a plethora of IoT devices while maintaining low transmission latency for bursty data. The simulation results show that PPUSA can support up to 600,000 IoT devices when the NB-IoT uplink utilization is 80%. In addition, it takes only one millisecond for the transmission of the bursty messages. Full article

(This article belongs to the Special Issue Feature Papers in the Sensor Networks Section 2022)

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27 pages, 869 KiB

Open AccessReview

Static-Analysis-Based Solutions to Security Challenges in Cloud-Native Systems: Systematic Mapping Study

by Md Shahidur Rahaman, Agm Islam, Tomas Cerny and Shaun Hutton

Sensors 2023, 23(4), 1755; https://doi.org/10.3390/s23041755 - 4 Feb 2023

Cited by 5 | Viewed by 5162

Abstract

Security is a significant priority for cloud-native systems, regardless of the system size and complexity. Therefore, one must utilize a set of defensive mechanisms or controls to protect the system from exploitation by potential adversaries. There is an expanding amount of research on security issues, including attacks against individual microservices or overall systems and their corresponding defense mechanism options. This study intends to provide a comprehensive overview of currently used defense mechanisms involving static analysis that can detect and react against associated attacks and vulnerabilities. We present a systematic literature review that extracts current approaches for the security analysis of microservices and the violation of security principles. We gathered 1049 relevant publications, of which 50 were selected as primary studies. We are providing practitioners and developers with a structured survey of the existing literature of defensive solutions for microservice architectures and cloud-native systems to aid them in identifying applicable solutions for their systems. Full article

(This article belongs to the Special Issue Feature Papers in the Sensor Networks Section 2022)

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