Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200995
Konstantinos Tsachrelias, A. Gkamas, Chrysostomos-Athanasios Katsigiannis, Christos Bouras, V. Kokkinos, P. Pouyioutas
In previous years, 3G and 4G cellular homogeneous networks configured with macro Base Stations (BSs) relied only on the downlink signal, even though transmission power and interference levels differ significantly between uplink and downlink. In 5G Heterogeneous Networks (HetNet), a new generation which have multiple BSs of different types such as Femto BS and Macro BS, there is the possibility of choosing to receive the data from one BS and transmit them to a different BS, and therefore decoupling the uplink and downlink. Especially, the increasing demand for faster, more reliable, and efficient connectivity has made the optimization of User Equipment (UE) allocation in 5G networks a crucial task. To tackle the challenges posed by heterogeneous 5G networks, this study compares and evaluates the performance of Downlink/Uplink Decoupling (DUDe) and traditional Downlink/Uplink Coupled (DUCo) user allocation approaches. Simulation results show that DUDe UE allocation outperforms DUCo by providing improved network performance and more efficient utilization of network resources in diverse network conditions. These findings have important implications for the design and optimization of 5G networks and provide valuable insights for researchers and practitioners in the field.
{"title":"On the Optimization of User Allocation in Heterogeneous 5G Networks Using DUDe Techniques","authors":"Konstantinos Tsachrelias, A. Gkamas, Chrysostomos-Athanasios Katsigiannis, Christos Bouras, V. Kokkinos, P. Pouyioutas","doi":"10.1109/ICUFN57995.2023.10200995","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200995","url":null,"abstract":"In previous years, 3G and 4G cellular homogeneous networks configured with macro Base Stations (BSs) relied only on the downlink signal, even though transmission power and interference levels differ significantly between uplink and downlink. In 5G Heterogeneous Networks (HetNet), a new generation which have multiple BSs of different types such as Femto BS and Macro BS, there is the possibility of choosing to receive the data from one BS and transmit them to a different BS, and therefore decoupling the uplink and downlink. Especially, the increasing demand for faster, more reliable, and efficient connectivity has made the optimization of User Equipment (UE) allocation in 5G networks a crucial task. To tackle the challenges posed by heterogeneous 5G networks, this study compares and evaluates the performance of Downlink/Uplink Decoupling (DUDe) and traditional Downlink/Uplink Coupled (DUCo) user allocation approaches. Simulation results show that DUDe UE allocation outperforms DUCo by providing improved network performance and more efficient utilization of network resources in diverse network conditions. These findings have important implications for the design and optimization of 5G networks and provide valuable insights for researchers and practitioners in the field.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"118 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":"114974511","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/ICUFN57995.2023.10200213
Y. Choi, J. Baek, Jin Hong Kim, Joon-Goo Lee
This paper proposes an edge camera system for a vehicle detection system using AI local optimization method utilizing minimal network transmission data. Currently, various AI CCTVs are installed, but if they are installed in an area without data network support, updates are slow and optimization is difficult. We improve traffic object recognition by remotely optimizing the detector with minimal data in a 3G or so communication environment, and use it to estimate the speed and location of the vehicle. Local AI optimizer utilizes optimized weight data using DBs using environmental data-based background images, and vehicle speed estimation utilizes warping data-based tracking data. We confirmed the high sensing performance and speed recognition rate through certification exam of the proposed edge camera system.
{"title":"Development of Edge Camera System for Vehicle Detection System Using Local AI Optimizer Based on Minimum Network Resource","authors":"Y. Choi, J. Baek, Jin Hong Kim, Joon-Goo Lee","doi":"10.1109/ICUFN57995.2023.10200213","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200213","url":null,"abstract":"This paper proposes an edge camera system for a vehicle detection system using AI local optimization method utilizing minimal network transmission data. Currently, various AI CCTVs are installed, but if they are installed in an area without data network support, updates are slow and optimization is difficult. We improve traffic object recognition by remotely optimizing the detector with minimal data in a 3G or so communication environment, and use it to estimate the speed and location of the vehicle. Local AI optimizer utilizes optimized weight data using DBs using environmental data-based background images, and vehicle speed estimation utilizes warping data-based tracking data. We confirmed the high sensing performance and speed recognition rate through certification exam of the proposed edge camera system.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"15 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":"115274457","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/ICUFN57995.2023.10199909
Duc-Nghia Vu, Nhu-Ngoc Dao, Dongwook Won, Sungrae Cho
The evolution of wireless networks has transformed the way people interact and communicate with each other. The next generation of wireless technology, 6G, promises to take this evolution to the next level. In this paper, we present an overview of the key technologies that are likely to shape the future of 6G mobile networks such as terahertz communication, visible light communication, ultra-massive MIMO, artificial intelligence, quantum communication, blockchain, and intelligent reflective surface. We discuss the unique advantages and challenges associated with each technology and provide examples of ongoing research to overcome these challenges. By leveraging these technologies, 6G networks have the potential to provide ultra-high data rates, ultra-reliable low-latency communication, and massive connectivity to support a wide range of emerging applications, including virtual and augmented reality, autonomous vehicles, smart cities, and more. The integration of these technologies has the potential to enable new use cases, unlock new opportunities, and bring us closer to realizing the full potential of the 6G vision.
{"title":"Potential Enabling Technologies for 6G Mobile Communication Networks: A Recent Review","authors":"Duc-Nghia Vu, Nhu-Ngoc Dao, Dongwook Won, Sungrae Cho","doi":"10.1109/ICUFN57995.2023.10199909","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199909","url":null,"abstract":"The evolution of wireless networks has transformed the way people interact and communicate with each other. The next generation of wireless technology, 6G, promises to take this evolution to the next level. In this paper, we present an overview of the key technologies that are likely to shape the future of 6G mobile networks such as terahertz communication, visible light communication, ultra-massive MIMO, artificial intelligence, quantum communication, blockchain, and intelligent reflective surface. We discuss the unique advantages and challenges associated with each technology and provide examples of ongoing research to overcome these challenges. By leveraging these technologies, 6G networks have the potential to provide ultra-high data rates, ultra-reliable low-latency communication, and massive connectivity to support a wide range of emerging applications, including virtual and augmented reality, autonomous vehicles, smart cities, and more. The integration of these technologies has the potential to enable new use cases, unlock new opportunities, and bring us closer to realizing the full potential of the 6G vision.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"21 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":"127450206","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/ICUFN57995.2023.10200692
Jae Hyung Jung, Kangyoon Lee
This paper represents PLL (Phase Locked Loop) for dual band communication of NB-IoT and LPWAIoT, of which the Band width is 699MHz to 960MHz, 1710MHz to 2170MHz. The lock time of the PLL improved by combining the digital operation with analog when tracking the target frequency. In the proposed PLL architecture, many techniques are used to fasten lock time, to cover the wide range of the VCO (Voltage Controlled Oscillator) for the QPSK (Quaternary Phase Shift Keying) communication. The proposed PLL is designed with 65nm CMOS technology and covers the operating frequency range from 2624 MHz to 4471 MHz with a reference clock frequency of 30.72 MHz. The measured phase noise performance of the proposed PLL is 106.15 dBc/Hz at a VCO output frequency of 4.34 GHz at an offset frequency of 1MHz.
{"title":"Fast Locking Dual Band PLL for NB-IoT with QPSK Modulation","authors":"Jae Hyung Jung, Kangyoon Lee","doi":"10.1109/ICUFN57995.2023.10200692","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200692","url":null,"abstract":"This paper represents PLL (Phase Locked Loop) for dual band communication of NB-IoT and LPWAIoT, of which the Band width is 699MHz to 960MHz, 1710MHz to 2170MHz. The lock time of the PLL improved by combining the digital operation with analog when tracking the target frequency. In the proposed PLL architecture, many techniques are used to fasten lock time, to cover the wide range of the VCO (Voltage Controlled Oscillator) for the QPSK (Quaternary Phase Shift Keying) communication. The proposed PLL is designed with 65nm CMOS technology and covers the operating frequency range from 2624 MHz to 4471 MHz with a reference clock frequency of 30.72 MHz. The measured phase noise performance of the proposed PLL is 106.15 dBc/Hz at a VCO output frequency of 4.34 GHz at an offset frequency of 1MHz.","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":"125158950","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/ICUFN57995.2023.10199497
M. Hossain, Tangina Sultana, Ga-Won Lee, E. Huh
The Internet of Things (IoT) is a rapidly growing field, encompassing various devices and sensors that produce enormous quantities of data. On the other hand, microservices architecture has emerged as a popular solution for developing complex software applications on a large scale. Combining these two technologies has the potential to revolutionize the creation of powerful and scalable IoT applications. By leveraging the benefits of microservices, such as modularity and decoupling, developers can design more flexible, scalable, and resilient IoT systems. In this paper, we present a thorough analysis of the state-of-the-art research regarding the use of microservices in the development of IoT systems. We summarize thirty selected studies and discuss their contributions to the field. Additionally, this paper offers valuable insights into the use of microservices in IoT applications, which can inform the design and development of future IoT systems. Finally, we outline and explain the future research opportunities that the microservices paradigm can offer in the context of the IoT.
{"title":"The Role of Microservices in the Internet of Things: Applications, Challenges, and Research Opportunities","authors":"M. Hossain, Tangina Sultana, Ga-Won Lee, E. Huh","doi":"10.1109/ICUFN57995.2023.10199497","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199497","url":null,"abstract":"The Internet of Things (IoT) is a rapidly growing field, encompassing various devices and sensors that produce enormous quantities of data. On the other hand, microservices architecture has emerged as a popular solution for developing complex software applications on a large scale. Combining these two technologies has the potential to revolutionize the creation of powerful and scalable IoT applications. By leveraging the benefits of microservices, such as modularity and decoupling, developers can design more flexible, scalable, and resilient IoT systems. In this paper, we present a thorough analysis of the state-of-the-art research regarding the use of microservices in the development of IoT systems. We summarize thirty selected studies and discuss their contributions to the field. Additionally, this paper offers valuable insights into the use of microservices in IoT applications, which can inform the design and development of future IoT systems. Finally, we outline and explain the future research opportunities that the microservices paradigm can offer in the context of the IoT.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"196 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":"115185494","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/ICUFN57995.2023.10199790
Samuel Kakuba, Dong Seog Han
The interactive speech between two or more inter locutors involves the text and acoustic modalities. These modalities consist of intra and cross-modality relationships at different time intervals which if modeled well, can avail emotionally rich cues for robust and accurate prediction of emotion states. This necessitates models that take into consideration long short-term dependency between the current, previous, and future time steps using multimodal approaches. Moreover, it is important to contextualize the interactive speech in order to accurately infer the emotional state. A combination of recurrent and/or convolutional neural networks with attention mechanisms is often used by researchers. In this paper, we propose a deep learning-based bimodal speech emotion recognition (DLBER) model that uses multi-level fusion to learn intra and cross-modality feature representations. The proposed DLBER model uses the transformer encoder to model the intra-modality features that are combined at the first level fusion in the local feature learning block (LFLB). We also use self-attentive bidirectional LSTM layers to further extract intramodality features before the second level fusion for further progressive learning of the cross-modality features. The resultant feature representation is fed into another self-attentive bidirectional LSTM layer in the global feature learning block (GFLB). The interactive emotional dyadic motion capture (IEMOCAP) dataset was used to evaluate the performance of the proposed DLBER model. The proposed DLBER model achieves 72.93% and 74.05% of F1 score and accuracy respectively.
{"title":"Bimodal Speech Emotion Recognition using Fused Intra and Cross Modality Features","authors":"Samuel Kakuba, Dong Seog Han","doi":"10.1109/ICUFN57995.2023.10199790","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199790","url":null,"abstract":"The interactive speech between two or more inter locutors involves the text and acoustic modalities. These modalities consist of intra and cross-modality relationships at different time intervals which if modeled well, can avail emotionally rich cues for robust and accurate prediction of emotion states. This necessitates models that take into consideration long short-term dependency between the current, previous, and future time steps using multimodal approaches. Moreover, it is important to contextualize the interactive speech in order to accurately infer the emotional state. A combination of recurrent and/or convolutional neural networks with attention mechanisms is often used by researchers. In this paper, we propose a deep learning-based bimodal speech emotion recognition (DLBER) model that uses multi-level fusion to learn intra and cross-modality feature representations. The proposed DLBER model uses the transformer encoder to model the intra-modality features that are combined at the first level fusion in the local feature learning block (LFLB). We also use self-attentive bidirectional LSTM layers to further extract intramodality features before the second level fusion for further progressive learning of the cross-modality features. The resultant feature representation is fed into another self-attentive bidirectional LSTM layer in the global feature learning block (GFLB). The interactive emotional dyadic motion capture (IEMOCAP) dataset was used to evaluate the performance of the proposed DLBER model. The proposed DLBER model achieves 72.93% and 74.05% of F1 score and accuracy respectively.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"66 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":"114567320","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/ICUFN57995.2023.10199172
Seunghan Choi, Changki Kim
These days, due to the increase in the use of mobile terminals such as smartphones, tablets, and XRM(Extended Reality and Media) service terminals, heterogeneous networks for various services are often connected to the 5G network. Low latency should be supported on the network for these services. At the time of measuring the latency at the current time point, recalculating the end-to-end QoS path, or informing the XRM service application, it can be a past value, which can lead to an inaccurate situation. To overcome this situation, 5G network needs to predict latency in advance, recalculate end-to-end QoS paths based on this information, or informs XRM applications to meet more effective QoS requirements. In this paper, we have evaluated the performance of several machine learning models for predicting latency, and introduce the results of experimenting with performance.
{"title":"A Study on Latency Prediction in 5G network","authors":"Seunghan Choi, Changki Kim","doi":"10.1109/ICUFN57995.2023.10199172","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199172","url":null,"abstract":"These days, due to the increase in the use of mobile terminals such as smartphones, tablets, and XRM(Extended Reality and Media) service terminals, heterogeneous networks for various services are often connected to the 5G network. Low latency should be supported on the network for these services. At the time of measuring the latency at the current time point, recalculating the end-to-end QoS path, or informing the XRM service application, it can be a past value, which can lead to an inaccurate situation. To overcome this situation, 5G network needs to predict latency in advance, recalculate end-to-end QoS paths based on this information, or informs XRM applications to meet more effective QoS requirements. In this paper, we have evaluated the performance of several machine learning models for predicting latency, and introduce the results of experimenting with performance.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"66 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":"114577516","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/icufn57995.2023.10199861
{"title":"Venue","authors":"","doi":"10.1109/icufn57995.2023.10199861","DOIUrl":"https://doi.org/10.1109/icufn57995.2023.10199861","url":null,"abstract":"","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":"121859561","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/ICUFN57995.2023.10200515
Min-Ki Kim, You-Ze Cho
With the development of the Internet, the number of users on mobile devices is increasing. However, mobile networks have a poor performance because of high round-trip time (RTT) variations. Much research has been conducted to overcome this, including active research on transport layer protocols. Google proposed a new transport protocol called QUIC and demonstrated that QUIC outperforms TCP in the real world. Furthermore, research on the multipath extension of QUIC (MPQUIC) is also being actively conducted. However, MPQUIC has poor performance in networks with high RTT variations caused by the weakness of the loss detection algorithm. In this paper, we improved the performance of MPQUIC by modifying MPQUIC’s time-based loss detection algorithm. We confirmed that the download completion time decreased by 55.5% compared with the original MPQUIC.
{"title":"D-MPQUIC: Optimizing Loss Detection in High RTT Variation Networks","authors":"Min-Ki Kim, You-Ze Cho","doi":"10.1109/ICUFN57995.2023.10200515","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200515","url":null,"abstract":"With the development of the Internet, the number of users on mobile devices is increasing. However, mobile networks have a poor performance because of high round-trip time (RTT) variations. Much research has been conducted to overcome this, including active research on transport layer protocols. Google proposed a new transport protocol called QUIC and demonstrated that QUIC outperforms TCP in the real world. Furthermore, research on the multipath extension of QUIC (MPQUIC) is also being actively conducted. However, MPQUIC has poor performance in networks with high RTT variations caused by the weakness of the loss detection algorithm. In this paper, we improved the performance of MPQUIC by modifying MPQUIC’s time-based loss detection algorithm. We confirmed that the download completion time decreased by 55.5% compared with the original MPQUIC.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"41 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":"116617530","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/ICUFN57995.2023.10200137
Syed Muhammad Ammar Hassan Bukhari, Muhammad Afaq, Wang-Cheol Song
With the advancement in network devices and the proliferation of new technologies such as Software-Defined Networking (SDN), managing a network becomes more difficult. In an SDN network, a single physical device acts as a firewall and load balancer at the same time. The management of those devices and the prevention of the resources being exhausted is a challenging task for the network administrator. In this direction, this paper presents an approach to predict resources on a switch in an SDN-based network. For this purpose, a video streaming scenario is deployed in an SDN network and performance metrics are captured. The resources are predicted using four machine learning algorithms. Specifically, the paper proposes a testbed implementation of a video streaming scenario to evaluate the performance of the proposed approach. The proposed approach can help network operators optimize network performance, ensure efficient use of resources, and enhance user experience.
{"title":"Streaming via SDN: Resource forecasting for video streaming in a Software-Defined Network","authors":"Syed Muhammad Ammar Hassan Bukhari, Muhammad Afaq, Wang-Cheol Song","doi":"10.1109/ICUFN57995.2023.10200137","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200137","url":null,"abstract":"With the advancement in network devices and the proliferation of new technologies such as Software-Defined Networking (SDN), managing a network becomes more difficult. In an SDN network, a single physical device acts as a firewall and load balancer at the same time. The management of those devices and the prevention of the resources being exhausted is a challenging task for the network administrator. In this direction, this paper presents an approach to predict resources on a switch in an SDN-based network. For this purpose, a video streaming scenario is deployed in an SDN network and performance metrics are captured. The resources are predicted using four machine learning algorithms. Specifically, the paper proposes a testbed implementation of a video streaming scenario to evaluate the performance of the proposed approach. The proposed approach can help network operators optimize network performance, ensure efficient use of resources, and enhance user experience.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"18 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":"129873646","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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