• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.8
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• pp.796-804
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• 1992

This paper presents a design of a backbone network which uses a rigister-Insertion ring structure, The introduction of a high speed register in sertton backbone ring enables high performance inter-network 4ommunicatlons In a simple and modular structure at low cost and Its concurrent communications.. Two or more bridge nodes can be used to construct a register Insertion backbone ring network. The high bandwidth of the backbone ring sup ports heavy traffic for Inter-segment Eornrnunicatlons. The bridge node does both local address filtering to block data entering the ring and remote address filtering to block data entering the local LAN segment . Title local address greatly reduces the rate on the backbone ring and the remote address filterlng greatly reduces the traffic rate on each LAN segment. An feature makes the network the network reconflguratlon simpler and transparent to users. A throughput analysis Is used to deterrune the bandwidth of the backbone rlr)g transmission medium.

• Proceedings of the IEEK Conference
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• 2003.11c
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• pp.223-226
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• 2003

In this paper, we propose new agent discovery and route discovery schemes to support Mobile IP (MIP) in Ad Hoc networks with wireless backbone. The wireless backbone consisting of stationary wireless routers and Internet gateways (IGs) is a kind of wireless access network of IP-based core network. The proposed scheme utilizes favorable features of wireless backbone such as stable links and no energy constraints. In the agent discovery scheme, backbone-limited periodic Agent Advertisement (AA) and proxy-AA messages are used, which reduce network-wide broadcasting overhead caused by AA and Agent Solicitation messages and decentralize MIP processing overhead in IGs. In order to reduce delay time and control message overhead during route discovery far the destination outside Ad Hoc network, we propose a cache-based scheme which can be easily added to the conventional on-demand routing protocols. The proposed schemes can reduce control overhead during agent discovery and route discovery, and efficiently support MIP in Ad Hoc network with wireless backbone.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.3
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• pp.135-149
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• 2008

Traditional attack detection schemes based on packets or flows have very high computational complexity. And, network based anomaly detection schemes can reduce the complexity, but they have a limitation to figure out the pattern of the distributed global scale network attack. In this paper, we propose an efficient and fast method for detecting distributed global-scale network attack symptoms in high-speed backbone networks. The proposed method is implemented at the aggregate traffic level. So, our proposed scheme has much lower computational complexity, and is implemented in very high-speed backbone networks. In addition, the proposed method can detect attack patterns, such as attacks in which the target is a certain host or the backbone infrastructure itself, via collaboration of edge routers on the backbone network. The effectiveness of the proposed method are demonstrated via simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1416-1427
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• 2012

This paper proposes a design technique of a survivable ship backbone network, which describes a near optimal configuration scheme of physical and logical topologies of which the survivable ship backbone network consists. We first analyze and present an efficient architecture of a survivable ship backbone network consisting of redundant links and ship devices with dual communication interfaces. Then, we present an integer linear programming-based configuration scheme of a physical topology with regard to the proposed ship backbone network architecture. Finally, we present a metaheuristic-based configuration scheme of a logical topology, underlying the physical topology.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.21-29
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• 2020

Accurate estimation of human pose relies on backbone method in which its role is to extract feature map. Up to dated, the method of backbone feature extraction is conducted by the plain convolutional neural networks named by CNN and the residual neural networks named by Resnet, both of which have various architectures and performances. The CNN family network such as VGG which is well-known as a multiple stacked hidden layers architecture of deep learning methods, is base and simple while Resnet which is a bottleneck layers architecture yields fewer parameters and outperform. They have achieved inspired results as a backbone network in human pose estimation. However, they were used then followed by different pose estimation networks named by pose parsing module. Therefore, in this paper, we present a comparison between the plain CNN family network (VGG) and bottleneck network (Resnet) as a backbone method in the same pose parsing module. We investigate their performances such as number of parameters, loss score, precision and recall. We experiment them in the bottom-up method of human pose estimation system by adapted the pose parsing module of openpose. Our experimental results show that the backbone method using VGG network outperforms the Resent network with fewer parameter, lower loss score and higher accuracy of precision and recall.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.128-132
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• 2023

Recently, with the development of deep learning technology, research on pedestrian attribute recognition technology using deep neural networks has been actively conducted. Existing pedestrian attribute recognition techniques can be obtained in such a way as global-based, regional-area-based, visual attention-based, sequential prediction-based, and newly designed loss function-based, depending on how pedestrian attributes are detected. It is known that the performance of these pedestrian attribute recognition technologies varies greatly depending on the type of backbone network that constitutes the deep neural networks model. Therefore, in this paper, several backbone networks are applied to the baseline pedestrian attribute recognition model and the performance changes of the model are analyzed. In this paper, the analysis is conducted using Resnet34, Resnet50, Resnet101, Swin-tiny, and Swinv2-tiny, which are representative backbone networks used in the fields of image classification, object detection, etc. Furthermore, this paper analyzes the change in time complexity when inferencing each backbone network using a CPU and a GPU.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.106-118
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• 2019

In recent years, research and development on image object recognition using artificial intelligence have been actively carried out, and it is expected to be used for road maintenance. Among them, artificial intelligence models for object detection of road surface are continuously introduced. In order to develop such object recognition algorithms, a backbone network that extracts feature maps is essential. In this paper, we will discuss how to select the appropriate neural network. To accomplish it, we compared with 4 different deep neural networks using 6,000 road surface damage images. Based on three evaluation methods for analyzing characteristics of neural networks, we propose a method to determine optimal neural networks. In addition, we improved the performance through optimal tuning of hyper-parameters, and finally developed a light backbone network that can achieve 85.9% accuracy of road surface damage classification.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5B
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• pp.889-898
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• 2000

In order to support various broadband multimedia servies in the future, we designed a well balanced WDM backbone network. In Korean network traffic environment, six regional centers are selected, link capacities between the regional centers are estimated from the PDI traffic model, and the overall network configuration is designed for the all-optical backbone network. Also, we designed a basic configuration to be able to protect minimum communication capability against link failure. A simulation study is carried out to verify the desired performance of the designed WDM backbone network. Simulation results show that performance of the backbone network is well balanced to support various communication services in Korea in the mid 2000s

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1165-1173
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• 1999

In order to support various multimedia communication services, a well balanced backbone network should be designed using recently advanced optical communication technologies. In this paper an optimal backbone network configuration design is presented fur Korean traffic environment. A new traffic model, Population-Distance-Gross Group Products(PDG) traffic model, is devised. In Korean network traffic environment, six regional centers are selected, link capacities between the regional centers are estimated from the PDG traffic model, and the overall network configuration is designed for the all-optical backbone network in Korea. A simulation study is carried out to verify the desired performance of the designed backbone network. Simulation results show that performance of the backbone network is well balanced to support various communication services in Korea in the 2000s.

• 한국정보통신설비학회:학술대회논문집
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• 2004.08a
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• pp.59-62
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• 2004

차세대 지능형 광 전달망의 구축, 확산에 따라 새로운 개념의 L1 VPN인 Optical VPN에 대한 많은 연구가 이루어지고 있다. 현재까지의 Optical VPN은 OXC 시스템 제조업체가 제공하는 EMS/NMS의 부가 기능으로 구현되고 있으며 따라서 멀티 벤더 환경의 광 전달망 구조에서는 적용할 수 없는 문제점 있다. 본 논문에서는 표준화된 시그널링 인터페이스를 활용하여 이러한 문제점을 극복하고 CNM 및 bandwidth-on-demand 기능을 제공하는 새로운 Optical VPN 서비스 플랫폼의 개념 및 개발 현황을 소개한다.