Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200899
E. Macedo, L. D. Moraes
The Internet of Things (IoT) is paving the way for the development of Cyber-Physical Systems (CPS), the next step of the Internet evolution, which will allow the development of several new systems and applications. Likewise, urged by the adoption of 5G and Beyond networks, the massive, ubiquitous spread of interconnected IoT devices has increasingly exposed the vulnerability of data and related applications in an unprecedented way. If the security of any component in such systems gets compromised, affecting its trust with respect to others, an associated data leak may cause serious threats to privacy, material losses, and even put people’s lives at risk. In this paper, we present IoT devices’ traffic characterization to provide trust values to enable secure communications among such devices. We develop experiments using a real IoT dataset to demonstrate the feasibility and the effectiveness of our proposal. Considering that complementary features between blockchain technology and information theory triggers a great potential for research and innovation, the key idea of the contribution consists in modeling trust using a two-level approach, which is based on a distributed-ledger (at the high level), and a relative entropy measure (at the low level). The results show the feasibility of our approach.
{"title":"Traffic Characterization to Provide Trust for Internet of Things Devices","authors":"E. Macedo, L. D. Moraes","doi":"10.1109/ICUFN57995.2023.10200899","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200899","url":null,"abstract":"The Internet of Things (IoT) is paving the way for the development of Cyber-Physical Systems (CPS), the next step of the Internet evolution, which will allow the development of several new systems and applications. Likewise, urged by the adoption of 5G and Beyond networks, the massive, ubiquitous spread of interconnected IoT devices has increasingly exposed the vulnerability of data and related applications in an unprecedented way. If the security of any component in such systems gets compromised, affecting its trust with respect to others, an associated data leak may cause serious threats to privacy, material losses, and even put people’s lives at risk. In this paper, we present IoT devices’ traffic characterization to provide trust values to enable secure communications among such devices. We develop experiments using a real IoT dataset to demonstrate the feasibility and the effectiveness of our proposal. Considering that complementary features between blockchain technology and information theory triggers a great potential for research and innovation, the key idea of the contribution consists in modeling trust using a two-level approach, which is based on a distributed-ledger (at the high level), and a relative entropy measure (at the low level). The results show the feasibility of our approach.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128590377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200512
Chang-Su Lee, J. Um, Mi-Hyang Jeon
In order for various IoTs to share information and collaborate on the internet, a common use environment and a lot of data transmission are inevitable. In this study, a distributed platform was designed, and an application service was implemented in which IoTs equipped with decentralized identifiers socialized with each other and collaborated using social networking. Distributed platforms can reduce network usage costs by reducing network traffic, and decentralization can increase the efficiency of shared information protection between IoTs.
{"title":"Design and implementation of autonomous collaboration service between IoT using distributed platform","authors":"Chang-Su Lee, J. Um, Mi-Hyang Jeon","doi":"10.1109/ICUFN57995.2023.10200512","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200512","url":null,"abstract":"In order for various IoTs to share information and collaborate on the internet, a common use environment and a lot of data transmission are inevitable. In this study, a distributed platform was designed, and an application service was implemented in which IoTs equipped with decentralized identifiers socialized with each other and collaborated using social networking. Distributed platforms can reduce network usage costs by reducing network traffic, and decentralization can increase the efficiency of shared information protection between IoTs.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128632675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200874
Su Yeol Kim, P. Kim
In this paper, a solar tracking system with feedback controller and state estimation filter is designed with consideration of unpredictable disturbance and feedback sensor noise and verified through various computer simulations. It is verified that the designed solar tracking system with PI controller and Kalman filter has the ability to reject disturbance and reduce feedback sensor noise.
{"title":"A Solar Tracking System Using Feedback Controller and State Estimation Filter","authors":"Su Yeol Kim, P. Kim","doi":"10.1109/ICUFN57995.2023.10200874","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200874","url":null,"abstract":"In this paper, a solar tracking system with feedback controller and state estimation filter is designed with consideration of unpredictable disturbance and feedback sensor noise and verified through various computer simulations. It is verified that the designed solar tracking system with PI controller and Kalman filter has the ability to reject disturbance and reduce feedback sensor noise.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126896252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10199386
W. Mao, Sung-Hua Chen, Yu-Tang Huang, Yao-Teng Yang, Po-Heng Chou
The rapid development of science and technology has improved the quality of people life. In recent years, the use of microcontrollers has increased due to the rise of edge computing. Based on low cost, low power consumption, and high stability, the controller can be widely used in various fields. In this research, an ARM-based platform is applied with a camera module to perform image recognition tasks. The MQTT protocol is realized to transmit the image recognition results. The MobileNets models are developed with X-CUBE-AI tool to perform transfer learning on indoor scene datasets. The verification results are obtained by training MobileNetV1 and MobileNetV2 structures. The proposed image system indeed achieves the average accuracies of 67.2% and 71.6% for MobileNetV1 and MobileNetV2, respectively.
{"title":"Indoor Scene Recognition Using ARM-based MobileNets Architectures","authors":"W. Mao, Sung-Hua Chen, Yu-Tang Huang, Yao-Teng Yang, Po-Heng Chou","doi":"10.1109/ICUFN57995.2023.10199386","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199386","url":null,"abstract":"The rapid development of science and technology has improved the quality of people life. In recent years, the use of microcontrollers has increased due to the rise of edge computing. Based on low cost, low power consumption, and high stability, the controller can be widely used in various fields. In this research, an ARM-based platform is applied with a camera module to perform image recognition tasks. The MQTT protocol is realized to transmit the image recognition results. The MobileNets models are developed with X-CUBE-AI tool to perform transfer learning on indoor scene datasets. The verification results are obtained by training MobileNetV1 and MobileNetV2 structures. The proposed image system indeed achieves the average accuracies of 67.2% and 71.6% for MobileNetV1 and MobileNetV2, respectively.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121639327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10201234
Hovhannes A. Harutyunyan, Narek A. Hovhannisyan, Edward Maraachlian
Broadcasting is an information dissemination problem in an interconnection network where one node, called the originator, must distribute a message to all other nodes by placing a series of calls along the links of the network. Every time the informed nodes aid the originator in distributing the message. Finding the broadcast time of any node in an arbitrary network is NP-complete. Polynomial time solutions are known only for a few classes of networks. In this paper, we consider chains of rings. We present a linear algorithm to find the broadcast time of arbitrary chains of rings and closed chains of rings.
{"title":"Broadcasting in chains of rings","authors":"Hovhannes A. Harutyunyan, Narek A. Hovhannisyan, Edward Maraachlian","doi":"10.1109/ICUFN57995.2023.10201234","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10201234","url":null,"abstract":"Broadcasting is an information dissemination problem in an interconnection network where one node, called the originator, must distribute a message to all other nodes by placing a series of calls along the links of the network. Every time the informed nodes aid the originator in distributing the message. Finding the broadcast time of any node in an arbitrary network is NP-complete. Polynomial time solutions are known only for a few classes of networks. In this paper, we consider chains of rings. We present a linear algorithm to find the broadcast time of arbitrary chains of rings and closed chains of rings.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114855364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10199670
Y. Jeon, C. Lee, Soon Ju Kang
With the COVID-19 pandemic and an aging population, there has been a rise in demand for homecare for patients with chronic diseases that require continuous monitoring outside of the hospital. One important bio-signal for such monitoring is an electrocardiogram (ECG), which measures the electrical activity of the heart and can detect dangerous conditions such as arrhythmias and myocardial infarctions. The application of deep learning classification algorithms to arrhythmia and myocardial infarction diagnosis has gained interest. However, to be effectively utilized in everyday life, a method to determine who performed the measurement is necessary. In this study, we evaluated the use of recurrence plot pre-processing and convolutional neural network (CNN) models to identify individuals based on their ECG signals. Our proposed method demonstrated high accuracy results across various CNN models and was capable of identifying individuals.
{"title":"Recurrence Plot based Person Identification with ECG using CNN model","authors":"Y. Jeon, C. Lee, Soon Ju Kang","doi":"10.1109/ICUFN57995.2023.10199670","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199670","url":null,"abstract":"With the COVID-19 pandemic and an aging population, there has been a rise in demand for homecare for patients with chronic diseases that require continuous monitoring outside of the hospital. One important bio-signal for such monitoring is an electrocardiogram (ECG), which measures the electrical activity of the heart and can detect dangerous conditions such as arrhythmias and myocardial infarctions. The application of deep learning classification algorithms to arrhythmia and myocardial infarction diagnosis has gained interest. However, to be effectively utilized in everyday life, a method to determine who performed the measurement is necessary. In this study, we evaluated the use of recurrence plot pre-processing and convolutional neural network (CNN) models to identify individuals based on their ECG signals. Our proposed method demonstrated high accuracy results across various CNN models and was capable of identifying individuals.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124492768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10199426
Hyun-Soon Nam, Jin-Kyu Choi, Jong-Kook Lee, Hea-Sook Park
Recently, according as most services have recently transitioned to supporting mobile service and existing services have been made it easier to access, there have been researches about using effectively wireless resources and increasing service processing speed. And research about network analysis technology becomes as a key area to configure and place complex and flexible network elements efficiently, and to include dynamically allocating and deallocating network resources to support quality of service for each service with service awareness.In this paper, in order to measure the performance data and quality data of each segment of the network in a wired and wireless convergence network, we describe architecture of the analysis system that manage divided into multiple segment according to characteristics and zone, and that integrate and analyze network various network quality characteristics, and that provides function to analyze network performance data using AI and function to optimize network resource management using the analysis results.
{"title":"Cloud Native Architecture Of Network Quality Characteristic Analysis System In Wired and Wireless Convergence Network","authors":"Hyun-Soon Nam, Jin-Kyu Choi, Jong-Kook Lee, Hea-Sook Park","doi":"10.1109/ICUFN57995.2023.10199426","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199426","url":null,"abstract":"Recently, according as most services have recently transitioned to supporting mobile service and existing services have been made it easier to access, there have been researches about using effectively wireless resources and increasing service processing speed. And research about network analysis technology becomes as a key area to configure and place complex and flexible network elements efficiently, and to include dynamically allocating and deallocating network resources to support quality of service for each service with service awareness.In this paper, in order to measure the performance data and quality data of each segment of the network in a wired and wireless convergence network, we describe architecture of the analysis system that manage divided into multiple segment according to characteristics and zone, and that integrate and analyze network various network quality characteristics, and that provides function to analyze network performance data using AI and function to optimize network resource management using the analysis results.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124011059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200885
Joohong Rheey, Hyunggon Park
The increasing popularity of Internet of Things (IoT) devices has brought significant security challenges to IoT networks. However, most deep learning-based anomaly detection solutions often require high computation performance so that it is difficult to be implanted on low-end IoT devices with limited power and memory capacity. In this paper, we propose a low-complexity network anomaly detection method based on feature selection using the Shapley value for the Isolation Forest algorithm. The proposed feature selection method using the Shapley value can reduce the dimension of input data, thereby improving the performance with reduced computational complexity. We provide simulation results to demonstrate the effectiveness of the proposed method. The results show that the proposed method based on Isolation Forest achieves comparable performance to the deep learning method based on neural networks while using fewer dimensions than the deep learning method.
{"title":"Low-complexity Anomaly Detection Method based on Feature Importance using Shapley Value","authors":"Joohong Rheey, Hyunggon Park","doi":"10.1109/ICUFN57995.2023.10200885","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200885","url":null,"abstract":"The increasing popularity of Internet of Things (IoT) devices has brought significant security challenges to IoT networks. However, most deep learning-based anomaly detection solutions often require high computation performance so that it is difficult to be implanted on low-end IoT devices with limited power and memory capacity. In this paper, we propose a low-complexity network anomaly detection method based on feature selection using the Shapley value for the Isolation Forest algorithm. The proposed feature selection method using the Shapley value can reduce the dimension of input data, thereby improving the performance with reduced computational complexity. We provide simulation results to demonstrate the effectiveness of the proposed method. The results show that the proposed method based on Isolation Forest achieves comparable performance to the deep learning method based on neural networks while using fewer dimensions than the deep learning method.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127556706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10199842
Kasun Prabhath, S. Jayaweera
The optimal beamformer weight update timing is derived for 3D beamforming between Unmanned Aerial Vehicles (UAVs). The use of optimal update period $(triangle t^{*})$ ensures that beamforming gain $(G_{tx})$ drops below a required threshold least frequently. When the exact flight path of the UAV receiver (UAV-RX) is available, the proposed optimization problem calculates optimal $triangle t^{*}$ exactly. It is shown that when the antenna aperture is fixed, the optimal $triangle t^{*}$ monotonically decreases as the operating frequency increases. As a result, the beamformer needs to be updated more often when using higher frequencies. However, it is shown that the fractional overhead relative to the large bandwidths available in mmWave spectrum can still be lower, justifying the use of mmWave frequencies in UAV-to-UAV communications. When exact flight path knowledge is not available, the proposed algorithm incorporates UAV-RX location predictions to update the beamforming weights in a timely manner. The proposed method was simulated in a UAV communication system and the performance of the system is analyzed in terms of the UAV-RX location prediction error. The findings indicate that when there are location prediction errors, incorporating a gain margin to the minimum gain threshold further enhances the algorithm’s performance by approximately 10-20%.
{"title":"Optimal Adaptation of 3D Beamformers in UAV Networks","authors":"Kasun Prabhath, S. Jayaweera","doi":"10.1109/ICUFN57995.2023.10199842","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199842","url":null,"abstract":"The optimal beamformer weight update timing is derived for 3D beamforming between Unmanned Aerial Vehicles (UAVs). The use of optimal update period $(triangle t^{*})$ ensures that beamforming gain $(G_{tx})$ drops below a required threshold least frequently. When the exact flight path of the UAV receiver (UAV-RX) is available, the proposed optimization problem calculates optimal $triangle t^{*}$ exactly. It is shown that when the antenna aperture is fixed, the optimal $triangle t^{*}$ monotonically decreases as the operating frequency increases. As a result, the beamformer needs to be updated more often when using higher frequencies. However, it is shown that the fractional overhead relative to the large bandwidths available in mmWave spectrum can still be lower, justifying the use of mmWave frequencies in UAV-to-UAV communications. When exact flight path knowledge is not available, the proposed algorithm incorporates UAV-RX location predictions to update the beamforming weights in a timely manner. The proposed method was simulated in a UAV communication system and the performance of the system is analyzed in terms of the UAV-RX location prediction error. The findings indicate that when there are location prediction errors, incorporating a gain margin to the minimum gain threshold further enhances the algorithm’s performance by approximately 10-20%.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126233315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200612
Dongheon Lee, Seongyeop Joung, Sooyong Choi
In massive multiple-input multiple-output (MIMO) systems, the channel state information (CSI) is needed to achieve high data rate. However, getting the CSI of the full antennas is hard since channel state information reference signal (CSI-RS) overhead is large. Therefore the CSI-RS port virtualization matrix which groups the antennas in a single CSI-RS port at the base station is used. In this paper, we propose a deep neural network (DNN) based CSI-RS port virtualization matrix design scheme for a time division duplex (TDD) massive MIMO system. The proposed scheme utilizes both the CSI-RS and sounding reference signal to get the CSI and estimates the CSI-RS port virtualization matrix in terms of codebook index. Simulation result shows that the proposed DNN based scheme can achieve up to 25.8% performance gain, particularly in high uplink signal-to-noise ratio regions where more accurate uplink channel information can be obtained.
{"title":"DNN-based CSI-RS Port Virtualization Matrix Design in Massive MIMO System","authors":"Dongheon Lee, Seongyeop Joung, Sooyong Choi","doi":"10.1109/ICUFN57995.2023.10200612","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200612","url":null,"abstract":"In massive multiple-input multiple-output (MIMO) systems, the channel state information (CSI) is needed to achieve high data rate. However, getting the CSI of the full antennas is hard since channel state information reference signal (CSI-RS) overhead is large. Therefore the CSI-RS port virtualization matrix which groups the antennas in a single CSI-RS port at the base station is used. In this paper, we propose a deep neural network (DNN) based CSI-RS port virtualization matrix design scheme for a time division duplex (TDD) massive MIMO system. The proposed scheme utilizes both the CSI-RS and sounding reference signal to get the CSI and estimates the CSI-RS port virtualization matrix in terms of codebook index. Simulation result shows that the proposed DNN based scheme can achieve up to 25.8% performance gain, particularly in high uplink signal-to-noise ratio regions where more accurate uplink channel information can be obtained.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130439333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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