• 정보처리학회논문지C
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• 제12C권6호
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• pp.839-846
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• 2005

최근 정보기술의 발달로 통신, 방송, 인터넷 등의 모든 서비스들이 하나의 네트워크로 통합되는 광대역 통합망이 등장하게 되었다. 그러나 이에 대한 역기능으로 다양한 위협이 등장하고 있으며, 그 중 인터넷 웜과 같은 악성 코드는 국가 기간망을 뒤흔드는 혼란을 초래할 수 있다. 본 논문은 고성능 네트워크 환경에서 웜 확산에 대한 정확한 예측을 그 목표로 한다. 이를 위해 인터넷 쉽게 적용 가능한 확산 모델을 살펴보고, 여러 인터넷 웜을 적용하여 인터넷 환경에서 동작 방식을 분석한다. 제안 모델은 웜 확산 단계와 대응 단계에 따른 영향을 분석하여 인터넷 웜의 확산 규모와 속도를 보다 정확하게 예측할 수 있다. 본 논문의 결과는 광대역 통합 네트워크와 같은 고성능 네트워크에도 적용할 수 있다.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.608-619
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• 2018

As distributed generation (DG) is connected to grid, there is new node-type occurring in distribution network. An efficient algorithm is proposed in this paper to calculate power flow for weakly meshed distribution network with DGs in different load models. The algorithm respectively establishes mathematical models focusing on the wind power, photovoltaic cell, fuel cell, and gas turbine, wherein the different DGs are respectively equivalent to PQ, PI, PQ (V) and PV node-type. When dealing with PV node, the algorithm adopts reactive power compensation device to correct power, and the reactive power allocation principle is proposed to determine reactive power initial value to improve convergence of the algorithm. In addition, when dealing with the weakly meshed network, the proposed algorithm, which builds path matrix based on loop-analysis and establishes incident matrix of node voltage and injection current, possesses good convergence and strong ability to process the loops. The simulation results in IEEE33 and PG&G69 node distribution networks show that with increase of the number of loops, the algorithm's iteration times will decrease, and its convergence performance is stronger. Clearly, it can be effectively used to solve the problem of power flow calculation for weakly meshed distribution network containing different DGs.

• 융합신호처리학회논문지
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• 제7권2호
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• pp.53-59
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• 2006

동적 신경망은 시스템 식별과 신호예측과 같이 temporal 신호처리가 요구되는 여러 분야에서 적용되어 왔다. 본 논문에서는 신경망의 동특성을 향상시키기 위해 순방향 다층 신경망의 히든 층에 감마(Gamma) 메모리 커넬을 사용하는 감마 신경망(GAM)을 제안하고, 적응필터로 제안된 신경망을 사용하여 비선형 적응예측을 다루고 있다. 제안된 신경망은 비선형 신호예측을 통해 평가되었으며, 예측성능의 상대적인 비교를 위해 순방향 신경망(FNN)과 리커런트 신경망(RNN)과 비교하였다. 시뮬레이션 결과에 의하면 GAM 신경망은 수렴속도와 예측의 정확도에서 이러한 신경망보다 더 우수한 동작을 수행함으로써, 제안된 신경망이 기존의 다층 신경망보다 비정적 신호에 대한 비선형 예측에 더 효과적인 예측모델임을 확인하였다.

• 인터넷정보학회논문지
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• 제22권6호
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• pp.1-8
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• 2021

With the rapid growth of intelligent devices and communication technologies, 5G network environment has become more heterogeneous and complex in terms of service management and orchestration. 5G architecture requires supportive technologies to handle the existing challenges for improving the Quality of Service (QoS) and the Quality of Experience (QoE) performances. Among many challenges, traffic steering is one of the key elements which requires critically developing an optimal solution for smart guidance, control, and reliable system. Mobile edge computing (MEC), software-defined networking (SDN), network functions virtualization (NFV), and deep learning (DL) play essential roles to complementary develop a flexible computation and extensible flow rules management in this potential aspect. In this proposed system, an accurate flow recommendation, a centralized control, and a reliable distributed connectivity based on the inspection of packet condition are provided. With the system deployment, the packet is classified separately and recommended to request from the optimal destination with matched preferences and conditions. To evaluate the proposed scheme outperformance, a network simulator software was used to conduct and capture the end-to-end QoS performance metrics. SDN flow rules installation was experimented to illustrate the post control function corresponding to DL-based output. The intelligent steering for network communication traffic is cooperatively configured in SDN controller and NFV-orchestrator to lead a variety of beneficial factors for improving massive real-time Internet of Things (IoT) performance.

• 한국통신학회논문지
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• 제30권3C호
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• pp.141-146
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• 2005

The authors investigate the convergence speed problem of nonlinear adaptive equalization. Convergence constraints and time constant of radial basis function network using stochastic gradient (RBF-SG) algorithm is analyzed and a method of making time constant independent of hidden-node output power by using sample-by-sample node output power estimation is derived. The method for estimating the node power is to use a single-pole low-pass filter. It is shown by simulation that the proposed algorithm gives faster convergence and lower minimum MSE than the RBF-SG algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.227-229
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• 2005

This paper proposes a method of implementation of digital convergence platform(DCP) which enable the service of broadcasting, communication, multimedia and home automation. Also digital convergence platform based on MPEG-21 multimedia framework can be a model to provide a distributed electronic commerce environment of multimedia and to manage of it. Platform hardware is implemented using a general purpose CPU and high performance digital signal processor and has peripheral units for network and multi I/O. It is able to run applications of multimedia which has variable formats on DSP. In addition, a personal transaction of multimedia packaged with MPEG-21 multimedia framework is provided on digital convergence platform. Like this, digital convergence platform bring up a new architecture of multimedia systems using a new generation network.

• 한국IT서비스학회:학술대회논문집
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• 한국IT서비스학회 2009년도 춘계학술대회
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• pp.588-592
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• 2009

The latest advances in great revolution for digital media and contents industries with Ubiquitous era. Because of spread and supply of various multimedia devices with combination digital with network, we need various type of digital contents. The Digital contents consists of Middleware industries, network business, contents service presenters and users. For supporting digital media. contents and media devices have been converging Digital contents convergence has been proceeding rapidly in media, broadcast and communication field. And also, whole Environment for these industries has been changing, too. Wee need another digital contents convergence for new type of products and services because of convergence of IT and broadcast. In addition, new business trends is very important about these new industrial change and developments with digital contents convergence.

• 융합보안논문지
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• 제4권2호
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• pp.53-60
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• 2004

본 논문에서는 무선 인터넷 환경에서 CHAP 인증 기법을 이용한 로밍 서비스 지원 방법을 기술한다. 이를 위해 특별히 GPRS 망으로 이동한 이동 ISP 망 가입자가 자신의 홈 ISP 망을 접속하여 인증을 받기 위한 기법을 제시한다 또 이동 ISP 망 가입자의 단말에서 정의되어야 할 인증 메시지 구조와 GPRS 망 게이트웨이에서 구현될 메시지 구조를 제시한다. 아울러 GGSN과 ISP 망간의 인증 메시지 구조를 정의하며 이들 제안된 내용에 대해 시험 환경 구축을 통해 실제 시뮬레이션 결과를 보였다.

• ETRI Journal
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• 제42권3호
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• pp.366-375
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• 2020

The network traffic prediction of a smart substation is key in strengthening its system security protection. To improve the performance of its traffic prediction, in this paper, we propose an improved gravitational search algorithm (IGSA), then introduce the IGSA into a wavelet neural network (WNN), iteratively optimize the initial connection weighting, scalability factor, and shift factor, and establish a smart substation network traffic prediction model based on the IGSA-WNN. A comparative analysis of the experimental results shows that the performance of the IGSA-WNN-based prediction model further improves the convergence velocity and prediction accuracy, and that the proposed model solves the deficiency issues of the original WNN, such as slow convergence velocity and ease of falling into a locally optimal solution; thus, it is a better smart substation network traffic prediction model.

• ETRI Journal
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• 제26권1호
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• pp.27-37
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• 2004

The architecture in a differentiated services (DiffServ) network is based on a simple model that applies a per-class service in the core node of the network. However, because the network behavior is simple, the network structure and provisioning is complicated. If a service provider wants dynamic provisioning or a better bandwidth guarantee, the differentiated services network must use a signaling protocol with QoS parameters or an admission control method. Unfortunately, these methods increase the complexity. To overcome the problems with complexity, we investigated scalable dynamic provisioning for admission control in DiffServ networks. We propose a new scalable $qDPM^2$ mechanism based on a centralized bandwidth broker and distributed measurement-based admission control and movable boundary bandwidth management to support heterogeneous QoS requirements in DiffServ networks.