• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1193-1200
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• 2000

A network topology has been an important factor for an efficient network management, but data collection for the network configuration has been done manually or semi automatically by a network administrator or an expert. Requirements to generate an intro-domain network topology ar usually either all IP addresses with subne $t^ernet mask or the network identification of all IP addresses. The amounts of traffic are generally high in the semi-automatic system due to using large number of low-level protocols and commands to get rather simple data. In this paper, we propose an algorithm which can be executed with only publicly available input. It can find all IP addresses as well as the network boundary of an intra-domain by using an intelligent method developed in this algorithm. The collected data will be used to draw a network map automatically by using a proposed network topology generation algorithm.hm.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.411-425
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• 2021

In this paper, a vehicle recognition algorithm based on deep convolutional neural network and compression dictionary is proposed. Firstly, the network structure of fine vehicle recognition based on convolutional neural network is introduced. Then, a vehicle recognition system based on multi-scale pyramid convolutional neural network is constructed. The contribution of different networks to the recognition results is adjusted by the adaptive fusion method that adjusts the network according to the recognition accuracy of a single network. The proportion of output in the network output of the entire multiscale network. Then, the compressed dictionary learning and the data dimension reduction are carried out using the effective block structure method combined with very sparse random projection matrix, which solves the computational complexity caused by high-dimensional features and shortens the dictionary learning time. Finally, the sparse representation classification method is used to realize vehicle type recognition. The experimental results show that the detection effect of the proposed algorithm is stable in sunny, cloudy and rainy weather, and it has strong adaptability to typical application scenarios such as occlusion and blurring, with an average recognition rate of more than 95%.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.149-156
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• 2010

As following the development of the USN technology, sensor node used in sensor network has capability of quick data process and storage to support efficient network configuration is enabled. In addition, tree-based structure was transformed to cluster in the construction of sensor network. However, query processing based on existing tree structure could be inefficient under the cluster-based network. In this paper, we suggest energy efficient query processing mechanism using filtering through data attribute classification in cluster-based sensor network. The suggestion mechanism use advantage of cluster-based network so reduce energy of query processing and designed more intelligent query dissemination. And, we prove excellence of energy efficient side with MATLab.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4572-4586
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• 2019

Mobile Edge Computing (MEC) and Information-Centric Networking (ICN) are essential network architectures for the future Internet. The advantages of MEC and ICN such as computation and storage capabilities at the edge of the network, in-network caching and named-data communication paradigm can greatly improve the quality of video streaming applications. However, the packet loss in wireless network environments still affects the video streaming performance and the existing loss recovery approaches in ICN does not exploit the capabilities of MEC. This paper proposes a Deep Learning based Loss Recovery Mechanism (DL-LRM) for video streaming over MEC based ICN. Different with existing approaches, the Forward Error Correction (FEC) packets are generated at the edge of the network, which dramatically reduces the workload of core network and backhaul. By monitoring network states, our proposed DL-LRM controls the FEC request rate by deep reinforcement learning algorithm. Considering the characteristics of video streaming and MEC, in this paper we develop content caching detection and fast retransmission algorithm to effectively utilize resources of MEC. Experimental results demonstrate that the DL-LRM is able to adaptively adjust and control the FEC request rate and achieve better video quality than the existing approaches.

• Journal of Information Processing Systems
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• v.2 no.2
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• pp.82-87
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• 2006

In spite of the rapid development of the public network, the variety of network-based developments currently raises numerous risks factors regarding copyright violation, the prohibition and distribution of digital media utilization, safe communication, and network security. Among these problems, multimedia data tend to increase in the distributed network environment. Hence, most image information has been transmitted in the form of digitalization. Therefore, the need for multimedia contents protection must be addressed. This paper is focused on possible solutions for multimedia contents security in the public network in order to prevent data modification by non-owners and to ensure safe communication in the distributed network environment. Accordingly, the Orthogonal Forward Wavelet Transform-based Scalable Digital Watermarking technique is proposed in this paper.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.558-567
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• 2015

In recent years, we have seen a proliferation of mobile-network-enabled smart objects, such as smart-phones and smart-watches, that form a cyber-physical integrated network to connect the cyber and physical worlds through the capabilities of sensing, communicating, and computing. Discovery of the relationship between smart objects is a critical and nontrivial task in cyber-physical integrated network applications. Aiming to find the most stable relationship in the heterogeneous and dynamic cyber-physical network, we propose a distributed and efficient relationship-discovery algorithm, called dynamically maximizing remaining unchanged time with minimum connected dominant set (DMRUT-MCDS) for constructing a backbone with the smallest scale infrastructure. In our proposed algorithm, the impact of the duration of the relationship is considered in order to balance the size and sustain time of the infrastructure. The performance of our algorithm is studied through extensive simulations and the results show that DMRUT-MCDS performs well in different distribution networks.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.58-63
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• 2022

Recently, the improvement of computational processing ability due to the rapid development of computing technology has greatly advanced the field of artificial intelligence, and research to apply it in various domains is active. In particular, in the national defense field, attention is paid to intelligent recognition among machine learning techniques, and efforts are being made to develop object identification and monitoring systems using artificial intelligence. To this end, various image processing technologies and object identification algorithms are applied to create a model that can identify friendly and enemy weapon systems and personnel in real-time. In this paper, we conducted image processing and object identification focused on tanks among various weapon systems. We initially conducted processing the tanks' image using a convolutional neural network, a deep learning technique. The feature map was examined and the important characteristics of the tanks crucial for learning were derived. Then, using YOLOv5 Network, a CNN-based object detection network, a model trained by labeling the entire tank and a model trained by labeling only the turret of the tank were created and the results were compared. The model and labeling technique we proposed in this paper can more accurately identify the type of tank and contribute to the intelligent recognition system to be developed in the future.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05b
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• pp.1305-1308
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• 2003

Mobile Network은 일정한 규모 이상의 이동성을 지원하는 네트워치를 말한다. Mobile IP는 표준 IP에 이동성을 지원하기 위한 기법이다. Mobile IPv4에서는 Mobile Network을 가상적인 하나의 Mobile Node처럼 취급하여 지원이 가능하다. 하지만, Mobile IPv6에서는 몇몇의 문제점으로 인하여 Mobile IPv4에서와 같은 접근이 어렵다. 이 논문에서는 Mobile IPv6환경에서 Mobile Network을 지원할 수 있는 기법을 제안하고 분석하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.10
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• pp.2605-2619
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• 1996

In this paper, we evaluated performance of mobile exchange control part. Queueing network model is used for modeling of mobile exchange control part. We developed a call control processing and location registration scenartio which has a message exchange function between processors in mobile exchange control part. A network symbol are used the simulation models that are composed of the initialization module, message generation module, message routing module, message processing module, message generation module, HIPC network processing module, output analysis module. as a result of computer simulation, we obtain the processor utilization, the mean queue length, the mean waiting time of control part based on call processing and location registration capacity. The call processing and location registration capacity is referred by thenumber of call attempts in the mobile exchange and must be satisfied with the quality of service(delay time).

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.10
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• pp.1518-1527
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• 1989

We proposed a technique to design a multimicrocomputer system for real-time parallel processing with an interconnection network which has good network latency time. In order to simplify the performance evaluation and the design procedure under the hard real-time constraints we defined network latency time which takes into account the queueing delays of the networks. We designed a dynamic interconnection network following the proposed technique, and the simulation results show that we can easily estimate the multimicrocomputer system's approximate performance using the defined network latency time before the actual design, so this definition can help the efficient design of the real-time parallel processing systems.