• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2005년도 한국컴퓨터종합학술대회 논문집 Vol.32 No.1 (A)
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• pp.160-162
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• 2005

IPsec Tunnel Mode를 이용하여 보안 네트워크를 구축 시, 네트워크 구성이 중복된 경우에는 중복되지 않도록 재구성해야 하는 문제가 있다. 본 논문에서는 IPSec Tunnel Mode 통신을 하고자 하는 두 네트워크가 중복된 경우, IPSec 네트워크 별칭 기법을 통하여, 이전 네트워크의 구성을 변경하지 않고 통신할 수 있는 방안을 제시한다.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.315-318
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• 2005

Lots of researches have been focusing on ubiquitous computing which means wherever, whenever, whatever the required information must be accessible. In ubiquitous computing environment, ubiquitous sensor network (USN) is the basis technology for gathering and transferring the required information. However sensor network characteristically has more severe vulnerability than the existing networks do. The paper presents operation of secure protocols for delivering information in secure in ubiquitous computing environment and show improvement of the secure transferring protocol.

• Journal of Information Processing Systems
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• 제8권1호
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• pp.1-20
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• 2012

The most important criterion for achieving the maximum performance in a wireless mesh network (WMN) is to limit the interference within the network. For this purpose, especially in a multi-radio network, the best option is to use non-overlapping channels among different radios within the same interference range. Previous works that have considered non-overlapping channels in IEEE 802.11a as the basis for performance optimization, have considered the link quality across all channels to be uniform. In this paper, we present a measurement-based study of link quality across all channels in an IEEE 802.11a-based indoor WMN test bed. Our results show that the generalized assumption of uniform performance across all channels does not hold good in practice for an indoor environment and signal quality depends on the geometry around the mesh routers.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 춘계학술대회
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• pp.317-320
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• 2009

At the present day, the use of containers crisscrossing seven seas and intercontinental transport has significantly increased and bringing the change on the shape of the world economy which we cannot be neglected. Additionally, with the recent technological advances in wireless sensor network (WSN) technologies, has providing an economically feasible monitoring solution to diverse application that allow us to envision the intelligent containers represent the next evolutionary development step in order to increase the efficiency, productivity, utilities, security and safe of containerized cargo shipping. This paper we present a comprehensive containerized cargo monitoring system which has adaptively embedded WSN technology into cargo logistic technology. We share the basic requirement for an autonomous logistic network that could provide optimum performance and a suite of algorithms for self-organization and bi-directional communication of a scalable large number of sensor node apply on container regardless inland and maritime transportation.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.16-24
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• 2024

With an increase in the relevance of next-generation integrated networking environments, the need to effectively utilize advanced networking techniques also increases. Specifically, integrating Software-Defined Networking (SDN) with Multi-access Edge Computing (MEC) is critical for enhancing network flexibility and addressing challenges such as security vulnerabilities and complex network management. SDN enhances operational flexibility by separating the control and data planes, introducing management complexities. This paper proposes a reinforcement learning-based network path optimization strategy within SDN environments to maximize performance, minimize latency, and optimize resource usage in MEC settings. The proposed Enhanced Proximal Policy Optimization (PPO)-based scheme effectively selects optimal routing paths in dynamic conditions, reducing average delay times to about 60 ms and lowering energy consumption. As the proposed method outperforms conventional schemes, it poses significant practical applications.

• 한국통신학회:학술대회논문집
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• 한국통신학회 2004년도 추계종합학술대회 논문 초록집
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• pp.320-320
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• 2004

• 인터넷정보학회논문지
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• 제23권5호
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• pp.17-23
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• 2022

Network slicing is a promising paradigm and significant evolution for adjusting the heterogeneous services based on different requirements by placing dynamic virtual network functions (VNF) forwarding graph (VNFFG) and orchestrating service function chaining (SFC) based on criticalities of Quality of Service (QoS) classes. In system architecture, software-defined networks (SDN), network functions virtualization (NFV), and edge computing are used to provide resourceful data view, configurable virtual resources, and control interfaces for developing the modified deep reinforcement learning agent (MDRL-A). In this paper, task requests, tolerable delays, and required resources are differentiated for input state observations to identify the non-critical/critical classes, since each user equipment can execute different QoS application services. We design intelligent slicing for handing the cross-domain resource with MDRL-A in solving network problems and eliminating resource usage. The agent interacts with controllers and orchestrators to manage the flow rule installation and physical resource allocation in NFV infrastructure (NFVI) with the proposed formulation of completion time and criticality criteria. Simulation is conducted in SDN/NFV environment and capturing the QoS performances between conventional and MDRL-A approaches.

• Journal of Information Processing Systems
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• 제18권3호
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• pp.443-456
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• 2022

An efficient and reasonable resource allocation strategy can greatly improve the service quality of Internet of Vehicles (IoV). However, most of the current allocation methods have overestimation problem, and it is difficult to provide high-performance IoV network services. To solve this problem, this paper proposes a network resource allocation strategy based on deep learning network model DDQN. Firstly, the method implements the refined modeling of IoV model, including communication model, user layer computing model, edge layer offloading model, mobile model, etc., similar to the actual complex IoV application scenario. Then, the DDQN network model is used to calculate and solve the mathematical model of resource allocation. By decoupling the selection of target Q value action and the calculation of target Q value, the phenomenon of overestimation is avoided. It can provide higher-quality network services and ensure superior computing and processing performance in actual complex scenarios. Finally, simulation results show that the proposed method can maintain the network delay within 65 ms and show excellent network performance in high concurrency and complex scenes with task data volume of 500 kbits.

• 한국정보과학회논문지:정보통신
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• 제34권5호
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• pp.379-388
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• 2007

최근 컴퓨터 기술과 네트워크 기술의 급속한 발전과 보급으로 유선환경에서뿐만 아니라 무선환경에서도 이동단말기를 이용하여 네트워크에 접속하여 다양한 작업을 수행할 수 있게 되었다. 사용자들이 네트워크를 통해 이용하는 다양한 어플리케이션들 중에 스트리밍 미디어를 이용하는 어플리케이션의 비중이 높아지고 있으며 이는 유선환경뿐만 아니라 무선환경에서도 마찬가지이다. 스트리밍 미디어는 다른 데이타들에 비해 크기가 매우 크고 높은 네트워크 대역폭과 많은 컴퓨팅 자원을 필요로 한다. 스트리밍 미디어 서비스를 낮은 대역폭과 적은 컴퓨팅 자원을 가지는 이동단말기를 통해 이용할 경우 사용자 환경에 맞게 특화된 서비스가 아니라면 안정적인 서비스를 제공받지 못할 것이다. 특히 이동단말기에서는 배터리를 통한 제한된 에너지 환경을 가지고 있으므로 스트리밍 미디어의 재생을 끝까지 보장하기 위해서는 실시간으로 변화되는 에너지에 대하여 적응적으로 스트리밍을 조절하여야 한다. 본 논문에서는 이동단말기를 위하여 스트리밍 미디어 서비스시에 이동단말기의 에너지 상태에 따라 전송되는 프레임의 수를 동적으로 조절하는 DFRC기법을 연구하였다. 제안하는 기법은 적은 컴퓨팅 자원을 사용하면서 동적으로 스트리밍을 조절하므로 사용자들에게 완전한 재생시간을 보장한다.

• 한국시뮬레이션학회논문지
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• 제15권3호
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• pp.1-9
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• 2006

현재 그리드 컴퓨팅은 네트워크 컴퓨팅 환경에서 대용량의 데이터와 엄청난 컴퓨팅의 문제를 해결하는데 매우 효과적인 해결책으로 각광받고 있다. 그리드는 애플리케이션을 여러 부분으로 나누어, 각 부분을 수많은 컴퓨터에서 동시에 수행함으로써 대규모 시뮬레이션 및 대용량 컴퓨팅을 실현할 수 있다. 그러나, 이를 위해서는 효과적인 자원 관리와 스케줄링 기법이 필요하다. 이 논문에서 우리는 분산된 그리드 컴퓨팅 환경에서의 자원관리와 스케줄링에 적용 가능한 그리드 거래망 모델을 제안하고 자율적인 자원 거래를 위한 가격 입찰 알고리즘을 소개한다. 우리는 모델의 효율성과 능력을 입증하기 위해 DEVSJAVA 모델링 & 시뮬레이션 환경 하에서 프로토타입 모델을 설계하고 실험하였다.