• Information and Communications Magazine
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• v.33 no.6
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• pp.9-17
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• 2016

본고에서는 5G 망에서의 서비스 요구사항을 만족하기 위한 구조로서 Network Slicing 구조를 제안하고 세부 적용방안을 기술한다. 이를 위해 5G 서비스를 우선 정의하고 그에 따른 서비스 요구사항을 도출한 후, 이러한 요구사항과 관련해 현재 망의 문제점에 대해 기술하고 망 개선을 위한 기술 요구사항을 정립한다. 특히, 5G에서의 중요성이 높아질 것으로 전망되고 있는 'Network Slicing'의 필요성 및 개념에 대해 서술한다. Network Slicing에 대한 제조사들의 솔루션 동향, 3GPP 등 단체의 표준화 동향, APN 방식의 P-LTE/DECOR/RAN Slicing 등 관련 기술의 발전 동향을 포함한 5G Network Slicing 주요 기술 동향에 대해서 알아본다. 또한, Slice의 관리 및 BSS/OSS등과의 연계를 위한 통신사업자 입장에서의 플랫폼 요구사항을 정리한다. 5G Network Slicing을 충족하기 위한 주요 기술로 C/U plane 분리구조, 범용 서버를 활용한 NFV/SDN, Edge 기반의 분산된 수평적 네트워크, 데이터 오프로딩 및 지연시간 절감을 위한 Edge Computing 등을 들 수 있고 효율적인 자원 관리를 위한 Orchestration 등에 대해서도 알아본다. 이를 기반으로 하여 사업자 입장에서 5G Core Network 기술을 선도함은 물론이고 향후, 조기 상용화를 위한 진화 방향을 제시하고자 한다.

• ETRI Journal
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• v.44 no.2
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• pp.194-207
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• 2022

In the last decade, substantial progress has been achieved in intelligent traffic control technologies to overcome consistent difficulties of traffic congestion and its adverse effect on smart cities. Edge computing is one such advanced progress facilitating real-time data transmission among vehicles and roadside units to mitigate congestion. An edge computing-based deep reinforcement learning system is demonstrated in this study that appropriately designs a multiobjective reward function for optimizing different objectives. The system seeks to overcome the challenge of evaluating actions with a simple numerical reward. The selection of reward functions has a significant impact on agents' ability to acquire the ideal behavior for managing multiple traffic signals in a large-scale road network. To ascertain effective reward functions, the agent is trained withusing the proximal policy optimization method in several deep neural network models, including the state-of-the-art transformer network. The system is verified using both hypothetical scenarios and real-world traffic maps. The comprehensive simulation outcomes demonstrate the potency of the suggested reward functions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4849-4864
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• 2019

Modern applications such as augmented reality, connected vehicles, video streaming and gaming have stringent requirements on latency, bandwidth and computation resources. The explosion in data generation by mobile devices has further exacerbated the situation. Mobile Edge Computing (MEC) is a recent addition to the edge computing paradigm that amalgamates the cloud computing capabilities with cellular communications. The concept of MEC is to relocate the cloud capabilities to the edge of the network for yielding ultra-low latency, high computation, high bandwidth, low burden on the core network, enhanced quality of experience (QoE), and efficient resource utilization. In this paper, we provide a comprehensive overview on different traits of MEC including its use cases, architecture, computation offloading, security, economic aspects, research challenges, and potential future directions.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.136-141
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• 1994

In this paper, we implemented an opto-electronical signal processing system for the edge detection using the diffusion neural network. The diffusion neural network performs a Gaussian and DOG operation efficiently by the diffusion process. The diffusion neural network is more efficient than the LOG masking method in hardware implementation because it has a few connections and the connection weights are fixed-valued. We implemented a diffusion neural network using the characteristics of the light intensity distribution function which is similar to the Gaussian function. We have shown that the system can detect the edge of an image exactly through the experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.316-321
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• 2007

We propose a quatitative annotation method for edges in Bayesian networks using given sets of condition-specific data. Bayesian network model has been used widely in various fields to infer probabilistic dependency relationships between entities in target systems. Besides the need for identifying dependency relationships, the annotation of edges in Bayesian networks is required to analyze the meaning of learned Bayesian networks. We assume the training data is composed of several condition-specific data sets. The contribution of each condition-specific data set to each edge in the learned Bayesian network is measured using the ratio of likelihoods between network structures of including and missing the specific edge. The proposed method can be a good approach to make quantitative annotation for learned Bayesian network structures while previous annotation approaches only give qualitative one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1B
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• pp.31-38
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• 2012

In this paper, we propose a method to improve cell edge users' performance in HetNet (heterogeneous network) systems by cooperatively transmitting signals using remote radio heads (RRHs) located near coverage boundaries, referred to as edge RRHs. The proposed method locates the edge RRHs in specific locations of the cell boundary and provides an efficient operational strategy by adjusting the duty cycle of the edge RRHs and base stations. The effectiveness of the method is demonstrated by experimental performance based on the system model parameters of the CoMP (coordinated multi-point transmission and reception) scenario, which is discussed in LTE-Advanced (Long Term Evolution - Advanced) standard contributions. When compared with conventional methods, utilization of edge RRHs is especially advantageous for the performance improvement of lower percentile users in terms of average throughput and effectively improves the fairness among users.

• Journal of KIISE:Information Networking
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• v.29 no.1
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• pp.31-39
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• 2002

The VPN(Virtual Private Network) is a private network constructed logically on a public network infrastructure. There have been numerous studies to support the VPN services by using different technologies such as IP in IP, GRE, L2TP, MPLS and so on. Among these technologies, MPLS has shown many merits in aspects of QoS, security, and management, compared with other technologies. As an enhancement of the VPN that is controlled by MPLS PE(Provider Edge) routers, this paper presents the VPN controlled by MPLS CE(Customer Edge) routers. The functional architecture of the CE based VPN and operations of the CE routers are described along with the performance comparison of CE based MPLS VPN. It has been shown that the CE based VPN has more advantages than PE based VPN with respect to independency, scalability, security, and complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.450-470
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• 2023

Traditional cloud computing faces some challenges such as huge energy consumption, network delay and single point of failure. Edge computing is a typical distributed processing platform which includes multiple edge servers closer to the users, thus is more robust and can provide real-time computing services. Although outsourcing data to edge servers can bring great convenience, it also brings serious security threats. In order to provide image retrieval while ensuring users' data privacy, a privacy preserving image retrieval scheme in edge environment is proposed. Considering the distributed characteristics of edge computing environment and the requirement for lightweight computing, we present a privacy-preserving image retrieval scheme in edge computing environment, which two or more "honest but curious" servers retrieve the image quickly and accurately without divulging the image content. Compared with other traditional schemes, the scheme consumes less computing resources and has higher computing efficiency, which is more suitable for resource-constrained edge computing environment. Experimental results show the algorithm has high security, retrieval accuracy and efficiency.

• Convergence Security Journal
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• v.14 no.7
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• pp.37-43
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• 2014

Today, group research efforts are increasing for cutting edge technologies related to climate, radio astronomy, co-utilization of high performance computing resources and more. Accordingly, networks for cutting-edge researches a re also regarded as means for cutting-edge researches nowadays. Therefore, it is necessary for administrating cutti ng-edge network to be considered, reflecting such a current trend. In this sense, 'Research which can help to admin istrate the networks which are usually used as means for a lot researches' was set as a goal of this paper.

• ETRI Journal
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• v.30 no.5
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• pp.723-728
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• 2008

In this paper, a simple transmission line model for an edge-coupled patch antenna is presented. The coupled section is modeled with a lump network which represents the mutual admittance between patches and from patch to ground. Theoretical analysis of two edge-coupled patch antenna models are compared by simulation and experiment in antennas designed to operate at the 2 GHz band. The proposed model predicts the return loss of the antenna accurately.