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23 pages, 6124 KiB

Open AccessArticle

Design of Edge-IoMT Network Architecture with Weight-Based Scheduling

by Li-Min Tseng, Ping-Feng Chen and Chih-Yu Wen

Sensors 2023, 23(20), 8553; https://doi.org/10.3390/s23208553 - 18 Oct 2023

Cited by 1 | Viewed by 1032

Population health monitoring based on the Internet of Medical Things (IoMT) is becoming an important application trend healthcare improvement. This work aims to develop an autonomous network architecture, collecting sensor data with a cluster topology, forwarding information through relay nodes, and applying edge [...] Read more.

Population health monitoring based on the Internet of Medical Things (IoMT) is becoming an important application trend healthcare improvement. This work aims to develop an autonomous network architecture, collecting sensor data with a cluster topology, forwarding information through relay nodes, and applying edge computing and transmission scheduling for network scalability and operational efficiency. The proposed distributed network architecture incorporates data compression technologies and effective scheduling algorithms for handling the transmission scheduling of various physiological signals. Compared to existing scheduling mechanisms, the experimental results depict the network performance and show that in analyzing the delay and jitter, the proposed WFQ-based algorithms have reduced the delay and jitter ratio by about 40% and 19.47% compared to LLQ with priority queueing scheme, respectively. The experimental results also demonstrate that the proposed network topology is more effective than the direct path transmission approach in terms of energy consumption, which suggests that the proposed network architecture may improve the development of medical applications with body area networks such that the goal of self-organizing population health monitoring can be achieved. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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16 pages, 3926 KiB

Open AccessArticle

Car Bumper Effects in ADAS Sensors at Automotive Radar Frequencies

by Isabel Expósito, Ingo Chin, Manuel García Sánchez, Iñigo Cuiñas and Jo Verhaevert

Sensors 2023, 23(19), 8113; https://doi.org/10.3390/s23198113 - 27 Sep 2023

Viewed by 1912

Abstract

Radars in the W-band are being integrated into car bumpers for functionalities such as adaptive cruise control, collision avoidance, or lane-keeping. These Advanced Driving Assistance Systems (ADAS) enhance traffic security in coordination with Intelligent Transport Systems (ITS). This paper analyzes the attenuation effect [...] Read more.

Radars in the W-band are being integrated into car bumpers for functionalities such as adaptive cruise control, collision avoidance, or lane-keeping. These Advanced Driving Assistance Systems (ADAS) enhance traffic security in coordination with Intelligent Transport Systems (ITS). This paper analyzes the attenuation effect that car bumpers cause on the signals passing through them. Using the free-space transmission technique inside an anechoic chamber, we measured the attenuation caused by car bumper samples with different material compositions. The results show level drops lower than 1.25 dB in all the samples analyzed. The signal attenuation triggered by the bumpers decreases with the frequency, with differences ranging from 0.55 dB to 0.86 dB when comparing the end frequencies within the radar band. Among the analyzed bumper samples, those with a thicker varnish layer or with talc in the composition seem to attenuate more. We also provide an estimation of the measurement uncertainty for the validation of the obtained results. Uncertainty analysis yields values below 0.21 dB with a 95% coverage interval in the measured frequency band. When comparing the measured value with its uncertainty, i.e., the relative uncertainty, the lower the frequency in the measured band, the more accurate the measurements seem to be. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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17 pages, 2029 KiB

Open AccessArticle

Deep Learning-Based Link Quality Estimation for RIS-Assisted UAV-Enabled Wireless Communications System

by Belayneh Abebe Tesfaw, Rong-Terng Juang, Li-Chia Tai, Hsin-Piao Lin, Getaneh Berie Tarekegn and Kabore Wendenda Nathanael

Sensors 2023, 23(19), 8041; https://doi.org/10.3390/s23198041 - 23 Sep 2023

Viewed by 1484

Abstract

In recent years, unmanned aerial vehicles (UAVs) have become a valuable platform for many applications, including communication networks. UAV-enabled wireless communication faces challenges in complex urban and dynamic environments. UAVs can suffer from power limitations and path losses caused by non-line-of-sight connections, which [...] Read more.

In recent years, unmanned aerial vehicles (UAVs) have become a valuable platform for many applications, including communication networks. UAV-enabled wireless communication faces challenges in complex urban and dynamic environments. UAVs can suffer from power limitations and path losses caused by non-line-of-sight connections, which may hamper communication performance. To address these issues, reconfigurable intelligent surfaces (RIS) have been proposed as helpful technologies to enhance UAV communication networks. However, due to the high mobility of UAVs, complex channel environments, and dynamic RIS configurations, it is challenging to estimate the link quality of ground users. In this paper, we propose a link quality estimation model using a gated recurrent unit (GRU) to assess the link quality of ground users for a multi-user RIS-assisted UAV-enabled wireless communication system. Our proposed framework uses a time series of user channel data and RIS phase shift information to estimate the quality of the link for each ground user. The simulation results showed that the proposed GRU model can effectively and accurately estimate the link quality of ground users in the RIS-assisted UAV-enabled wireless communication network. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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16 pages, 776 KiB

Open AccessArticle

Adaptive Clustering of Users in Power Domain NOMA

by Yuri P. Santos and Luiz F. Q. Silveira

Sensors 2023, 23(11), 5314; https://doi.org/10.3390/s23115314 - 3 Jun 2023

Cited by 5 | Viewed by 1743

Abstract

By enabling multiple non-orthogonal transmissions, power domain non-orthogonal multiple access (PD-NOMA) potentially increases a system’s spectral efficiency. This technique can become an alternative for future generations of wireless communication networks. The efficiency of this method fundamentally depends on two previous processing steps: an [...] Read more.

By enabling multiple non-orthogonal transmissions, power domain non-orthogonal multiple access (PD-NOMA) potentially increases a system’s spectral efficiency. This technique can become an alternative for future generations of wireless communication networks. The efficiency of this method fundamentally depends on two previous processing steps: an appropriate grouping of users (transmission candidates) as a function of the channel gains and the choice of power levels that will be used to transmit each signal. Thus far, the solutions presented in the literature to address the problems of user clustering and power allocation do not consider the dynamics of communication systems, i.e., the temporal variation in the number of users and the channel conditions. In order to consider these dynamic characteristics in the clustering of users in NOMA systems, this work proposes a new clustering technique based on a modification of the DenStream evolutionary algorithm, chosen for its evolutionary capacity, noise robustness and online processing. We evaluated the performance of the proposed clustering technique considering, for simplicity, the use of an already widely known power allocation strategy called improved fractional strategy power allocation (IFSPA). The results show that the proposed clustering technique can follow the system dynamics, clustering all users and favoring the uniformity of the transmission rate between the clusters. Compared to orthogonal multiple access (OMA) systems, the proposed model’s gain was approximately 10%, obtained on a challenging communication scenario for NOMA systems since the channel model adopted does not favor a large difference in the channel gains between users. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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31 pages, 6557 KiB

Open AccessArticle

LM²K Model for Hosting an Application Based on Microservices in Multi-Cloud

by Juliana Carvalho, Dario Vieira, Christiano Rodrigues and Fernando Trinta

Sensors 2023, 23(9), 4450; https://doi.org/10.3390/s23094450 - 2 May 2023

Cited by 1 | Viewed by 1192

Abstract

Cloud computing has become a popular delivery model service, offering several advantages. However, there are still challenges that need to be addressed when applying the cloud model to specific scenarios. Two of such challenges involve deploying and executing applications across multiple providers, each [...] Read more.

Cloud computing has become a popular delivery model service, offering several advantages. However, there are still challenges that need to be addressed when applying the cloud model to specific scenarios. Two of such challenges involve deploying and executing applications across multiple providers, each comprising several services with similar functionalities and different capabilities. Therefore, dealing with application distributions across various providers can be a complex task for a software architect due to the differing characteristics of the application components. Some works have proposed solutions to address the challenges discussed here, but most of them focus on service providers. To facilitate the decision-making process of software architects, we previously presented PacificClouds, an architecture for managing the deployment and execution of applications based on microservices and distributed in a multi-cloud environment. Therefore, in this work, we focus on the challenges of selecting multiple clouds for PacificClouds and choosing providers that best meet the microservices and software architect requirements. We propose a selection model and three approaches to address various scenarios. We evaluate the performance of the approaches and conduct a comparative analysis of them. The results demonstrate their feasibility regarding performance. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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16 pages, 2498 KiB

Open AccessArticle

Resilience of Multi-Layer Communication Networks

by Vesa Kuikka and Heikki Rantanen

Sensors 2023, 23(1), 86; https://doi.org/10.3390/s23010086 - 22 Dec 2022

Cited by 2 | Viewed by 2209

Abstract

Advances in the future communication technologies and capabilities of new services in heterogeneous network systems have increased the need for modelling and analysing various aspects of both the resilience of networked systems and usability from the user’s point of view. We extend the [...] Read more.

Advances in the future communication technologies and capabilities of new services in heterogeneous network systems have increased the need for modelling and analysing various aspects of both the resilience of networked systems and usability from the user’s point of view. We extend the traditional network reliability theory to cover a wider scope of quality requirements and applications. The proposed method can be used to model the resilience of different structured networks, and the quality of information services. We use the term resilience to cover both the technical and quality-of-service aspects of user requirements. The modelling method is demonstrated with a use case of a multilayer communication network system. However, the method can be used to model any kind of technological network, such as wireless, sensor, and backbone networks. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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18 pages, 2240 KiB

Open AccessArticle

A 40 MHz 11-Bit ENOB Delta Sigma ADC for Communication and Acquisition Systems

by Hussein Fakhoury, Chadi Jabbour and Van-Tam Nguyen

Sensors 2023, 23(1), 36; https://doi.org/10.3390/s23010036 - 20 Dec 2022

Cited by 1 | Viewed by 1717

Abstract

This paper describes a Delta Sigma ADC IC that embeds a 5th-order Continuous-Time Delta Sigma modulator with 40 MHz signal bandwidth, a low ripple 20 to 80 MS/s variable-rate digital decimation filter, a bandgap voltage reference, and high-speed CML buffers on a single [...] Read more.

This paper describes a Delta Sigma ADC IC that embeds a 5th-order Continuous-Time Delta Sigma modulator with 40 MHz signal bandwidth, a low ripple 20 to 80 MS/s variable-rate digital decimation filter, a bandgap voltage reference, and high-speed CML buffers on a single die. The ADC also integrates on-chip calibrations for RC time-constant variation and quantizer offset. The chip was fabricated in a 1P7M 65 nm CMOS process. Clocked at 640 MHz, the Continuous-Time Delta Sigma modulator achieves 11-bit ENOB and 76.5 dBc THD up to 40 MHz of signal bandwidth while consuming 82.3 mW. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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22 pages, 1696 KiB

Open AccessArticle

Performance Analysis of Existing ITS Technologies: Evaluation and Coexistence

by Sassi Maaloul, Hasnaa Aniss, Leo Mendiboure and Marion Berbineau

Sensors 2022, 22(24), 9570; https://doi.org/10.3390/s22249570 - 7 Dec 2022

Cited by 3 | Viewed by 1272

Abstract

The performance of vehicular communication technologies changes dynamically according to the application requirements considering data rate, communication ranges, latency, etc. These applications are evolving rapidly and should enhance intelligent transport systems (ITS) such as road safety and automated driving. However, to reach the [...] Read more.

The performance of vehicular communication technologies changes dynamically according to the application requirements considering data rate, communication ranges, latency, etc. These applications are evolving rapidly and should enhance intelligent transport systems (ITS) such as road safety and automated driving. However, to reach the required quality, these applications need many radio resources to carry the potential traffic load resulting from the environmental perception and data exchanged between the different entities. Therefore, an assessment of vehicular communication technologies’ reliability and resilience under these conditions is required to address the multiple challenges of the ITS services. The paper’s main contribution is to propose a comprehensive analysis model able to evaluate and compare the performances of ITS technologies according to different constraints related to environment-changing situations. This analysis examines the channel occupancy and provides simulation results which allow the identification of the suitable configurations and the most appropriate technology for a given use case. We also propose a coexistence solution between these technologies based on density-sharing according to the use case requirements and the availability of the technology. Finally, we present the challenge of adaptive configuration in vehicular networks, which helps to provide the optimal structure through road profiles and environment variability (infrastructure, data, etc.). Results show different trade offs and limitations between the considered ITS technologies, which are essential to understand their behaviour in a realistic environment. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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17 pages, 671 KiB

Open AccessArticle

Resource Allocation in Downlink VLC-NOMA Systems for Factory Automation Scenario

by Won-Jae Ryu, Jae-Woo Kim and Dong-Seong Kim

Sensors 2022, 22(23), 9407; https://doi.org/10.3390/s22239407 - 2 Dec 2022

Cited by 4 | Viewed by 1307

Abstract

Industry 4.0 requires high-speed data exchange that includes fast, reliable, low-latency, and cost-effective data transmissions. As visible light communication (VLC) can provide reliable, low-latency, and secure connections that do not penetrate walls and are immune to electromagnetic interference; it can be considered a [...] Read more.

Industry 4.0 requires high-speed data exchange that includes fast, reliable, low-latency, and cost-effective data transmissions. As visible light communication (VLC) can provide reliable, low-latency, and secure connections that do not penetrate walls and are immune to electromagnetic interference; it can be considered a solution for Industry 4.0. The non-orthogonal multiple access (NOMA) technique can achieve high spectral efficiency using the same frequency and time resources for multiple users. It means that smaller amounts of resources will be used compared with orthogonal multiple access (OMA). Therefore, handling multiple data transmissions with VLC-NOMA can be easier for factory automation than OMA. However, as the transmit power is split, the reliability is reduced. Therefore, this study proposed a deep neural network (DNN)-based power-allocation algorithm (DBPA) to improve the reliability of the system. Further, to schedule multiple nodes in VLC-NOMA system, a priority-based user-pairing (PBUP) scheme is proposed. The proposed techniques in VLC-NOMA system were evaluated in terms of the factory automation scenario and showed that it improves reliability and reduces missed deadlines. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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19 pages, 2134 KiB

Open AccessArticle

Deep Learning in the Detection of Disinformation about COVID-19 in Online Space

by Kristína Machová, Marián Mach and Michal Porezaný

Sensors 2022, 22(23), 9319; https://doi.org/10.3390/s22239319 - 30 Nov 2022

Cited by 4 | Viewed by 1522

Abstract

This article focuses on the problem of detecting disinformation about COVID-19 in online discussions. As the Internet expands, so does the amount of content on it. In addition to content based on facts, a large amount of content is being manipulated, which negatively [...] Read more.

This article focuses on the problem of detecting disinformation about COVID-19 in online discussions. As the Internet expands, so does the amount of content on it. In addition to content based on facts, a large amount of content is being manipulated, which negatively affects the whole society. This effect is currently compounded by the ongoing COVID-19 pandemic, which caused people to spend even more time online and to get more invested in this fake content. This work brings a brief overview of how toxic information looks like, how it is spread, and how to potentially prevent its dissemination by early recognition of disinformation using deep learning. We investigated the overall suitability of deep learning in solving problem of detection of disinformation in conversational content. We also provided a comparison of architecture based on convolutional and recurrent principles. We have trained three detection models based on three architectures using CNN (convolutional neural networks), LSTM (long short-term memory), and their combination. We have achieved the best results using LSTM (F1 = 0.8741, Accuracy = 0.8628). But the results of all three architectures were comparable, for example the CNN+LSTM architecture achieved F1 = 0.8672 and Accuracy = 0.852. The paper offers finding that introducing a convolutional component does not bring significant improvement. In comparison with our previous works, we noted that from all forms of antisocial posts, disinformation is the most difficult to recognize, since disinformation has no unique language, such as hate speech, toxic posts etc. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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15 pages, 2312 KiB

Open AccessArticle

The (In)effectiveness of Attention Guidance Methods for Enhancing Brand Memory in 360° Video

by Jani Pavlič and Tina Tomažič

Sensors 2022, 22(22), 8809; https://doi.org/10.3390/s22228809 - 15 Nov 2022

Cited by 5 | Viewed by 1668

Abstract

Sensing and remembering features in visual scenes are conditioned by visual attention and methods to guide it. This should be relevant in terms of product placement, which has become an important part of incorporating brands into different mass media formats with a commercial [...] Read more.

Sensing and remembering features in visual scenes are conditioned by visual attention and methods to guide it. This should be relevant in terms of product placement, which has become an important part of incorporating brands into different mass media formats with a commercial purpose. The approach can be challenging in 360° video, where an omnidirectional view enables consumers to choose different viewing perspectives, which may result in overlooking the brands. Accordingly, attention guidance methods should be applied. This study is the first to explore diegetic guidance methods as the only appropriate guiding method for an unobtrusive and unconscious nature of product placement. To test the effectiveness of three different diegetic guiding methods, a between-subject design was employed, where the participants were assigned randomly to one of four videos with the same scene but different guiding methods. The findings show and explain the discrepancy with studies on guiding attention in other contexts, as there were no significant differences between the guiding cues according to brand recall and brand recognition. The results also indicate a significant influence of brand familiarity on brand recall in 360° video. The article concludes by providing limitations, future research directions, and recommendations for audiovisual policy. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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17 pages, 831 KiB

Open AccessArticle

Modulation Awareness Method for Dual-Hop Cooperative Transmissions over Frequency-Selective Channels

by Mohamed Marey and Hala Mostafa

Sensors 2022, 22(14), 5441; https://doi.org/10.3390/s22145441 - 21 Jul 2022

Cited by 2 | Viewed by 1556

Abstract

Modulation awareness and cooperative transmissions have individually received a significant amount of research in the scholarly literature. However, a limited number of works are principally concerned with the combination of the two topics, and they are restricted to frequency-flat wireless channels. In this [...] Read more.

Modulation awareness and cooperative transmissions have individually received a significant amount of research in the scholarly literature. However, a limited number of works are principally concerned with the combination of the two topics, and they are restricted to frequency-flat wireless channels. In this study, we propose a new modulation awareness method applicable to dual-hop amplify-and-forward cooperative broadcasts. The suggested method is built on the creation of theoretical representations of cross-correlation functions of the received signals. We conceptually prove that a family of modulation types generates spikes for certain cross-correlation functions, while others do not. We create a numerous layer hypothesis evaluation for the purpose of making judgments centered on this attribute. The suggested method has a number of benefits, such as the ability to operate on both frequency-flat and frequency-selective channels, as well as the absence of the necessity of channel awareness or noise power. Computer simulations analyze the performance of the proposed method, which delivers adequate awareness performance in a variety of operational scenarios. Full article

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17 pages, 4310 KiB

Open AccessArticle

A Fairness of Data Combination in Wireless Packet Scheduling

by Sovit Bhandari, Navin Ranjan, Yeong-Chan Kim, Pervez Khan and Hoon Kim

Sensors 2022, 22(4), 1658; https://doi.org/10.3390/s22041658 - 20 Feb 2022

Cited by 1 | Viewed by 1943

Abstract

With the proliferation of artificial intelligence (AI) technology, the function of AI in a sixth generation (6G) environment is likely to come into play on a large scale. Moreover, in recent years, with the rapid advancement in AI technology, the ethical issues of [...] Read more.

With the proliferation of artificial intelligence (AI) technology, the function of AI in a sixth generation (6G) environment is likely to come into play on a large scale. Moreover, in recent years, with the rapid advancement in AI technology, the ethical issues of AI have become a hot topic. In this paper, the ethical concern of AI in wireless networks is studied from the perspective of fairness in data. To make the dataset fairer, novel dataset categorization and dataset combination schemes are proposed. For the dataset categorization scheme, a deep-learning-based dataset categorization (DLDC) model is proposed. Based on the results of the DLDC model, the input dataset is categorized based on the group index. The datasets based on the group index are combined using various combination schemes. Through simulations, the results of each dataset combination method and their performance are compared, and the advantages and disadvantages of fairness and performance according to the dataset configuration are analyzed. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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22 pages, 7818 KiB

Open AccessArticle

An Ensemble Method for Missing Data of Environmental Sensor Considering Univariate and Multivariate Characteristics

by Chanyoung Choi, Haewoong Jung and Jaehyuk Cho

Sensors 2021, 21(22), 7595; https://doi.org/10.3390/s21227595 - 16 Nov 2021

Cited by 4 | Viewed by 2502

Abstract

With rapid urbanization, awareness of environmental pollution is growing rapidly and, accordingly, interest in environmental sensors that measure atmospheric and indoor air quality is increasing. Since these IoT-based environmental sensors are sensitive and value reliability, it is essential to deal with missing values, [...] Read more.

With rapid urbanization, awareness of environmental pollution is growing rapidly and, accordingly, interest in environmental sensors that measure atmospheric and indoor air quality is increasing. Since these IoT-based environmental sensors are sensitive and value reliability, it is essential to deal with missing values, which are one of the causes of reliability problems. Characteristics that can be used to impute missing values in environmental sensors are the time dependency of single variables and the correlation between multivariate variables. However, in the existing method of imputing missing values, only one characteristic has been used and there has been no case where both characteristics were used. In this work, we introduced a new ensemble imputation method reflecting this. First, the cases in which missing values occur frequently were divided into four cases and were generated into the experimental data: communication error (aperiodic, periodic), sensor error (rapid change, measurement range). To compare the existing method with the proposed method, five methods of univariate imputation and five methods of multivariate imputation—both of which are widely used—were used as a single model to predict missing values for the four cases. The values predicted by a single model were applied to the ensemble method. Among the ensemble methods, the weighted average and stacking methods were used to derive the final predicted values and replace the missing values. Finally, the predicted values, substituted with the original data, were evaluated by a comparison between the mean absolute error (MAE) and the root mean square error (RMSE). The proposed ensemble method generally performed better than the single method. In addition, this method simultaneously considers the correlation between variables and time dependence, which are characteristics that must be considered in the environmental sensor. As a result, our proposed ensemble technique can contribute to the replacement of the missing values generated by environmental sensors, which can help to increase the reliability of environmental sensor data. Full article

(This article belongs to the Special Issue Advances in Future Communication System)

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