SDN is a new network architecture that still faces traditional network attacks. Among the attacks, Distributed-Denial-of-Service is one of the most severe attacks, especially the TCP SYN Flooding attack, which has a more significant impact. This paper is mainly to mitigate the impact of the SYN Flood attack and will combine Kubernetes and design a unique component: SDN Controller Manager, which exists in K8s as a microservices. The proxy mechanism is used to resist the SYN Flooding attack, and the K8s feature is further utilized. If the SDN Controller Manager is attacked and the service is terminated abnormally, K8s will automatically create a new SDN Controller Manager component to continue to provide services.
SDN是一种新的网络架构，仍然面临着传统网络的攻击。在各种攻击中，分布式拒绝服务攻击是最严重的攻击之一，尤其是TCP SYN flood攻击，其影响更为显著。本文主要是为了减轻SYN Flood攻击的影响，将结合Kubernetes并设计一个独特的组件:SDN控制器管理器，它作为微服务存在于k8中。利用代理机制抵御SYN flood攻击，并进一步利用K8s特性。如果SDN Controller Manager受到攻击，导致服务异常终止，k8会自动创建新的SDN Controller Manager组件继续提供服务。
{"title":"Software-Defined Networking Integrated with Cloud Native and Proxy Mechanism: Detection and Mitigation System for TCP SYN Flooding Attack","authors":"Chun-I Fan, Jun-Huei Wang, Cheng-Han Shie, Yu-Lung Tsai","doi":"10.1109/IMCOM56909.2023.10035614","DOIUrl":"https://doi.org/10.1109/IMCOM56909.2023.10035614","url":null,"abstract":"SDN is a new network architecture that still faces traditional network attacks. Among the attacks, Distributed-Denial-of-Service is one of the most severe attacks, especially the TCP SYN Flooding attack, which has a more significant impact. This paper is mainly to mitigate the impact of the SYN Flood attack and will combine Kubernetes and design a unique component: SDN Controller Manager, which exists in K8s as a microservices. The proxy mechanism is used to resist the SYN Flooding attack, and the K8s feature is further utilized. If the SDN Controller Manager is attacked and the service is terminated abnormally, K8s will automatically create a new SDN Controller Manager component to continue to provide services.","PeriodicalId":230213,"journal":{"name":"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127505086","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 : 2023-01-03DOI: 10.1109/IMCOM56909.2023.10035665
Hui-Lin Yang, S. M. Raza, D. Le, Dongsoo S. Kim, Hyunseung Choo
Bike sharing is efficient urban mobility method as a user determines the rental period upon his/her demand. A dock-based sharing system designates places (i.e., bike docks or stations) where a user rents or returns a bike. Due to regionally and temporally erratic nature of urban mobility demand, bike imbalance among stations inevitably occurs and a service operator rebalances bikes to prevent service impairment. The precise prediction of imbalance for each station is essential to optimize the rebalancing schedule. This paper presents Dual-Branch Neural Networks (DBNNs) employing Long Short-Term Memory (LSTM) to classify the imbalance level of each station along with the prediction of bike counts. To address the dual objectives, the model trains by backpropagating both classification and prediction losses to the dual output branches individually, and jointly updates the trainable parameters of LSTM layers. The results showcase that the proposed model predicts bike counts within 8% average error for next 24 hours, and achieves 94% accuracy of classification for the same time period.
{"title":"Dual-Branch Neural Networks for Predicting Shared Bikes","authors":"Hui-Lin Yang, S. M. Raza, D. Le, Dongsoo S. Kim, Hyunseung Choo","doi":"10.1109/IMCOM56909.2023.10035665","DOIUrl":"https://doi.org/10.1109/IMCOM56909.2023.10035665","url":null,"abstract":"Bike sharing is efficient urban mobility method as a user determines the rental period upon his/her demand. A dock-based sharing system designates places (i.e., bike docks or stations) where a user rents or returns a bike. Due to regionally and temporally erratic nature of urban mobility demand, bike imbalance among stations inevitably occurs and a service operator rebalances bikes to prevent service impairment. The precise prediction of imbalance for each station is essential to optimize the rebalancing schedule. This paper presents Dual-Branch Neural Networks (DBNNs) employing Long Short-Term Memory (LSTM) to classify the imbalance level of each station along with the prediction of bike counts. To address the dual objectives, the model trains by backpropagating both classification and prediction losses to the dual output branches individually, and jointly updates the trainable parameters of LSTM layers. The results showcase that the proposed model predicts bike counts within 8% average error for next 24 hours, and achieves 94% accuracy of classification for the same time period.","PeriodicalId":230213,"journal":{"name":"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124875370","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 : 2023-01-03DOI: 10.1109/IMCOM56909.2023.10035609
Li-Hua Li, Radius Tanone
One of Indonesia's mainstay agricultural products is the potato. Disease prevention is essential for maintaining stable potato production. One technique for detecting disease in potatoes is to determine whether potato leaves are diseased (early blight or late blight) or healthy. Deep Learning models have been widely developed and used to classify disease recognition in potato leaves in the industrial era 4.0. Swin Transformer is a deep learning model based on transformers that is more efficient and accurate at solving classification problems. The Swin Transformer, a transformer based deep learning approach, is used in this study to identify diseases of the potato leaf. Moreover, several metrics including Precision, Recall, Accuracy, and F1 score, are used to assess the experimental results of the model we use. In terms of accuracy, the value obtained when training with this model is 97.70%. These findings indicate that using the Swin Transformer model to identify potato leaf diseases could be a new trend in agricultural research.
{"title":"Disease Identification in Potato Leaves using Swin Transformer","authors":"Li-Hua Li, Radius Tanone","doi":"10.1109/IMCOM56909.2023.10035609","DOIUrl":"https://doi.org/10.1109/IMCOM56909.2023.10035609","url":null,"abstract":"One of Indonesia's mainstay agricultural products is the potato. Disease prevention is essential for maintaining stable potato production. One technique for detecting disease in potatoes is to determine whether potato leaves are diseased (early blight or late blight) or healthy. Deep Learning models have been widely developed and used to classify disease recognition in potato leaves in the industrial era 4.0. Swin Transformer is a deep learning model based on transformers that is more efficient and accurate at solving classification problems. The Swin Transformer, a transformer based deep learning approach, is used in this study to identify diseases of the potato leaf. Moreover, several metrics including Precision, Recall, Accuracy, and F1 score, are used to assess the experimental results of the model we use. In terms of accuracy, the value obtained when training with this model is 97.70%. These findings indicate that using the Swin Transformer model to identify potato leaf diseases could be a new trend in agricultural research.","PeriodicalId":230213,"journal":{"name":"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133370737","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 : 2023-01-03DOI: 10.1109/IMCOM56909.2023.10035570
W. Liao, Yi-Shan Chang, Yi-Chieh Wu
The technology of generative adversarial networks (GAN) is constantly evolving, and synthesized images can no longer be accurately distinguished by the human eyes alone. GAN has been applied to the analysis of satellite images, mostly for the purpose of data augmentation. Recently, however, we have seen a twist in its usage. In information warfare, GAN has been used to create fake satellite images or modify the image content by putting fake bridges, buildings and clouds to mislead or conceal important intelligence. To address the increasing counterfeit cases in satellite images, the goal of this research is to develop algorithms that can classify fake remote sensing images robustly and efficiently. There exist many techniques to synthesize or manipulate the content of satellite images. In this paper, we focus on the case when the entire image is forged. Three satellite image synthesis methods, including ProGAN, cGAN and CycleGAN will be investigated. The effect of image pre-processing such as histogram equalization and bilateral filter will also be evaluated. Experiments show that satellite images generated by different GANs can be easily identified by individually trained models. The performance degraded when model trained with one type of GAN samples is employed to determine the originality of images synthesized with other types of GANs. Additionally, when histogram equalization is applied to the images, the detection model fails to distinguish its authenticity. A four-class universal classification model is proposed to address this issue. An overall accuracy of over 99% has been achieved even when pre-processing has been applied.
{"title":"Detection of Synthesized Satellite Images Using Deep Neural Networks","authors":"W. Liao, Yi-Shan Chang, Yi-Chieh Wu","doi":"10.1109/IMCOM56909.2023.10035570","DOIUrl":"https://doi.org/10.1109/IMCOM56909.2023.10035570","url":null,"abstract":"The technology of generative adversarial networks (GAN) is constantly evolving, and synthesized images can no longer be accurately distinguished by the human eyes alone. GAN has been applied to the analysis of satellite images, mostly for the purpose of data augmentation. Recently, however, we have seen a twist in its usage. In information warfare, GAN has been used to create fake satellite images or modify the image content by putting fake bridges, buildings and clouds to mislead or conceal important intelligence. To address the increasing counterfeit cases in satellite images, the goal of this research is to develop algorithms that can classify fake remote sensing images robustly and efficiently. There exist many techniques to synthesize or manipulate the content of satellite images. In this paper, we focus on the case when the entire image is forged. Three satellite image synthesis methods, including ProGAN, cGAN and CycleGAN will be investigated. The effect of image pre-processing such as histogram equalization and bilateral filter will also be evaluated. Experiments show that satellite images generated by different GANs can be easily identified by individually trained models. The performance degraded when model trained with one type of GAN samples is employed to determine the originality of images synthesized with other types of GANs. Additionally, when histogram equalization is applied to the images, the detection model fails to distinguish its authenticity. A four-class universal classification model is proposed to address this issue. An overall accuracy of over 99% has been achieved even when pre-processing has been applied.","PeriodicalId":230213,"journal":{"name":"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130714084","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 : 2023-01-03DOI: 10.1109/IMCOM56909.2023.10035568
J. Yoon, K. Kim, Tae-Jin Lee
In an indoor wireless network environment com-posed of Internet of Things (loT) devices, there can be devices that transmit data in a weak link due to obstacles and low transmission power. To solve the problem without additional energy consumption of devices, a new Medium Access Control (MAC) protocol is required for receiving data from the devices in the weak link. In this paper, we propose an energy-efficient MAC protocol that the AP can collect data by using a Hybrid- Reconfigurable Intelligent Surface (H - RIS). In the proposed network, the Access Point (AP) can distinguish the packet-level failure of the weak link and control the H - RIS to receive data from the device. Using simulations, we have shown that our proposed method can enhance the performance of the network throughput and energy efficiency of devices.
{"title":"Data Exchange Protocol for Weak Links with Hybrid-RIS in Wireless Networks","authors":"J. Yoon, K. Kim, Tae-Jin Lee","doi":"10.1109/IMCOM56909.2023.10035568","DOIUrl":"https://doi.org/10.1109/IMCOM56909.2023.10035568","url":null,"abstract":"In an indoor wireless network environment com-posed of Internet of Things (loT) devices, there can be devices that transmit data in a weak link due to obstacles and low transmission power. To solve the problem without additional energy consumption of devices, a new Medium Access Control (MAC) protocol is required for receiving data from the devices in the weak link. In this paper, we propose an energy-efficient MAC protocol that the AP can collect data by using a Hybrid- Reconfigurable Intelligent Surface (H - RIS). In the proposed network, the Access Point (AP) can distinguish the packet-level failure of the weak link and control the H - RIS to receive data from the device. Using simulations, we have shown that our proposed method can enhance the performance of the network throughput and energy efficiency of devices.","PeriodicalId":230213,"journal":{"name":"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126430622","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 : 2023-01-03DOI: 10.1109/IMCOM56909.2023.10035654
Dwynn Tama, Arya Wicaksana
Social media's decentralization gives users control of their data, contributing to privacy, ownership, and dissemination. The challenge is to develop a decentralized social media platform with the same features and performances as its centralized counterpart. This study aims to demonstrate and evaluate the performance of decentralized social media in terms of throughput and scalability. The prototype application is developed on NEAR (Near Protocol Blockchain), a non-EVM (Ethereum Virtual Machine) chain with sharding. The results show that the use of NEAR to store post content is not a scalable solution, and the workaround of using IndexedDB as a local database to store information reduces response time and increases throughput and scalability. Collaboration of on-chain and off-chain storage strategies performs better for decentralized social media applications.
{"title":"Performance Evaluation of Decentralized Social Media on Near Protocol Blockchain","authors":"Dwynn Tama, Arya Wicaksana","doi":"10.1109/IMCOM56909.2023.10035654","DOIUrl":"https://doi.org/10.1109/IMCOM56909.2023.10035654","url":null,"abstract":"Social media's decentralization gives users control of their data, contributing to privacy, ownership, and dissemination. The challenge is to develop a decentralized social media platform with the same features and performances as its centralized counterpart. This study aims to demonstrate and evaluate the performance of decentralized social media in terms of throughput and scalability. The prototype application is developed on NEAR (Near Protocol Blockchain), a non-EVM (Ethereum Virtual Machine) chain with sharding. The results show that the use of NEAR to store post content is not a scalable solution, and the workaround of using IndexedDB as a local database to store information reduces response time and increases throughput and scalability. Collaboration of on-chain and off-chain storage strategies performs better for decentralized social media applications.","PeriodicalId":230213,"journal":{"name":"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125077107","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 : 2023-01-03DOI: 10.1109/IMCOM56909.2023.10035576
S. Kim
We propose a novel covert communication technique between the federated learning (FL) server and participants without affecting the FL performance. The FL server superimposes the covert message onto the aggregated gradient and broadcasts the superimposed signal to all FL participants. FL participants decode the covert message treating the aggregated gradient as interference, and restore the original global model after removing the covert message from the superimposed signal. Therefore, the FL performance is not affected by sending the covert message. We analyze the covertness of communication against the adversary that monitors the statistical distribution of model updates. We derive the maximum achievable transmission rate of the covert message without being detected by the adversary and without affecting the federated learning performance.
{"title":"Covert Communication over Federated Learning Channel","authors":"S. Kim","doi":"10.1109/IMCOM56909.2023.10035576","DOIUrl":"https://doi.org/10.1109/IMCOM56909.2023.10035576","url":null,"abstract":"We propose a novel covert communication technique between the federated learning (FL) server and participants without affecting the FL performance. The FL server superimposes the covert message onto the aggregated gradient and broadcasts the superimposed signal to all FL participants. FL participants decode the covert message treating the aggregated gradient as interference, and restore the original global model after removing the covert message from the superimposed signal. Therefore, the FL performance is not affected by sending the covert message. We analyze the covertness of communication against the adversary that monitors the statistical distribution of model updates. We derive the maximum achievable transmission rate of the covert message without being detected by the adversary and without affecting the federated learning performance.","PeriodicalId":230213,"journal":{"name":"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121902640","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 : 2023-01-03DOI: 10.1109/IMCOM56909.2023.10035638
Ahmad Haiqal Abd Khalid, Nur Nazihah Mohkhlas, N. A. Zakaria, Mazidah Mat Rejab, Ruwinah Abdul Karim, Suharsiwi Suharsiwi
The enhancement of technology is well-developed and assistive technology is one of the foremost that has been used significantly. Individuals with disabilities use assistive technology to perform the desired activity that would otherwise be difficult or impossible. Mobility devices such as walkers and wheelchairs, as well as hardware, software, and peripherals that assist people with disabilities in accessing computers or other information technologies, are examples of assistive technology. Learning disabilities are caused by genetic and neurobiological factors that affect brain functioning, influencing one or more cognitive processes related to learning. This paper discusses a comprehensive systematic literature review (SLR) of the assistive technology (AT) for children with learning disabilities with combination of Kitchenham and PRISMA approach. This paper discusses on the assistive technologies developed for children with learning disabilities according to its type, purposes, techniques used, and platform or delivery system used to host the developed assistive technologies for children with learning disabilities.
{"title":"Assistive Technology for Children with Learning Disabilities: A Systematic Literature Review","authors":"Ahmad Haiqal Abd Khalid, Nur Nazihah Mohkhlas, N. A. Zakaria, Mazidah Mat Rejab, Ruwinah Abdul Karim, Suharsiwi Suharsiwi","doi":"10.1109/IMCOM56909.2023.10035638","DOIUrl":"https://doi.org/10.1109/IMCOM56909.2023.10035638","url":null,"abstract":"The enhancement of technology is well-developed and assistive technology is one of the foremost that has been used significantly. Individuals with disabilities use assistive technology to perform the desired activity that would otherwise be difficult or impossible. Mobility devices such as walkers and wheelchairs, as well as hardware, software, and peripherals that assist people with disabilities in accessing computers or other information technologies, are examples of assistive technology. Learning disabilities are caused by genetic and neurobiological factors that affect brain functioning, influencing one or more cognitive processes related to learning. This paper discusses a comprehensive systematic literature review (SLR) of the assistive technology (AT) for children with learning disabilities with combination of Kitchenham and PRISMA approach. This paper discusses on the assistive technologies developed for children with learning disabilities according to its type, purposes, techniques used, and platform or delivery system used to host the developed assistive technologies for children with learning disabilities.","PeriodicalId":230213,"journal":{"name":"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124775371","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 : 2023-01-03DOI: 10.1109/IMCOM56909.2023.10035605
Yong Wang, Yaqi Li, Dingsheng Wang
As the extraction of small water bodies in remote sensing images has problems such as water line interruption and pretzel phenomenon, in order to be able to improve the extraction accuracy of small water bodies, this paper proposes a small water body extraction method based on Res2Net- Unet. The method uses the encoder and decoder structure of the UNet model. Firstly, the ResNet-50 network of the Res2Net module is used as an encoder, thus exploiting the feature information at multiple scales in the image. Secondly, a hybrid domain attention mechanism is incorporated into the decoder structure to fully mine the spatial and channel features in the image. Finally, a jump connection is added between the encoder and decoder to better fuse the features extracted by the encoder and decoder. Experiments on the Chinese Gaofen-1(GF-1) image datasets from two study areas show that the method in this paper is feasible for more complete and more accurate extraction of small water bodies compared with common deep learning models.
{"title":"Extraction of small water body information based on Res2Net-Unet","authors":"Yong Wang, Yaqi Li, Dingsheng Wang","doi":"10.1109/IMCOM56909.2023.10035605","DOIUrl":"https://doi.org/10.1109/IMCOM56909.2023.10035605","url":null,"abstract":"As the extraction of small water bodies in remote sensing images has problems such as water line interruption and pretzel phenomenon, in order to be able to improve the extraction accuracy of small water bodies, this paper proposes a small water body extraction method based on Res2Net- Unet. The method uses the encoder and decoder structure of the UNet model. Firstly, the ResNet-50 network of the Res2Net module is used as an encoder, thus exploiting the feature information at multiple scales in the image. Secondly, a hybrid domain attention mechanism is incorporated into the decoder structure to fully mine the spatial and channel features in the image. Finally, a jump connection is added between the encoder and decoder to better fuse the features extracted by the encoder and decoder. Experiments on the Chinese Gaofen-1(GF-1) image datasets from two study areas show that the method in this paper is feasible for more complete and more accurate extraction of small water bodies compared with common deep learning models.","PeriodicalId":230213,"journal":{"name":"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129554764","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 : 2023-01-03DOI: 10.1109/IMCOM56909.2023.10035625
Dang Anh Khoa, Nguyen Trung Kiem, N. Kien, Nguyen Ngoc Tuan, Nguyen Huu Thanh
Software-Defined Networking (SDN) is gaining attention for its flexibility in programmability. It enhances network configuration and provides global visibility for administrators via a single interface. However, the centralized nature of SDN exposes many issues in scalability and resiliency. In this paper, with the advent of cloud computing, we present a containerized architecture capable of fast scaling up and down based on traffic load for SDN control plane. With our novel traffic-adaptive algorithm, the results show that the proposed system is able to fit performance with high incoming new-flow requests and scale down underused controllers for resource efficiency.
{"title":"Traffic-Adaptive Scheme for SDN Control Plane with Containerized Architecture","authors":"Dang Anh Khoa, Nguyen Trung Kiem, N. Kien, Nguyen Ngoc Tuan, Nguyen Huu Thanh","doi":"10.1109/IMCOM56909.2023.10035625","DOIUrl":"https://doi.org/10.1109/IMCOM56909.2023.10035625","url":null,"abstract":"Software-Defined Networking (SDN) is gaining attention for its flexibility in programmability. It enhances network configuration and provides global visibility for administrators via a single interface. However, the centralized nature of SDN exposes many issues in scalability and resiliency. In this paper, with the advent of cloud computing, we present a containerized architecture capable of fast scaling up and down based on traffic load for SDN control plane. With our novel traffic-adaptive algorithm, the results show that the proposed system is able to fit performance with high incoming new-flow requests and scale down underused controllers for resource efficiency.","PeriodicalId":230213,"journal":{"name":"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116482024","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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