• Journal of the Economic Geographical Society of Korea
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• v.13 no.2
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• pp.196-218
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• 2010

This study is to investigate the development process and the structure of the machine and material industrial clusters in Yeongnam region, Korea. In theoretical analysis, it is proposed that the wide area industrial cluster has three type of development process and a duplicate (or multi-level) spatial structure. We can ascertain from the case study of industrial clusters in Yeongnam region that An wide machine and material industrial cluster has been formed in Yeongnam region and the cluster has the duplicate structure or multi-level structure.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10a
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• pp.526-531
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• 2006

무선 인터넷 프록시 서버 클러스터는 성능 및 저장 공간의 확장성이 보장되어야 한다. 일반적으로 사용되는 RR 스케줄링의 경우 성능의 확장성은 보장되지만, 요청 URL 데이터의 중복 저장으로 인해 저장 공간의 확장성이 없는 단점을 가진다. 또한 저장 공간의 확장성을 위해 많이 사용되는 해싱 스케줄링의 경우, 요청 URL이 캐시 서버에 고정되어 있어 사용자의 요청 패턴 혹은 Hot-Spot 시에 성능의 확장성이 없는 단점을 가진다. 이에 본 논문에서는 성능 및 저장 공간의 확장성을 보장하는 새로운 동적 해싱 기법을 제안한다. 제안된 동적 해싱 기법은 캐시 서버의 부하 상태에 따라 요청 URL을 캐시 서버들 사이로 이동함으로써 사용자의 요청 패턴 혹은 Hot-Spot 시에 성능의 확장성을 보장한다. 제안된 방법은 16대의 컴퓨터를 사용하여 실험을 수행하였고, 실험 결과를 통해 제안된 방법이 기존 방법에 비해 성능 및 저장 공간의 확장성을 보장함을 확인하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.652-654
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• 2002

최근 리눅스 클러스터 시스템의 활용 범위가 커지면서 멀티미디어 서비스를 제공하려는 시도가 나타났다. 리눅스 클러스터 시스템 상에서 효과적으로 멀티미디어 서비스를 제공하려면 적합한 파일 시스템의 도움이 필수적이다. 즉, 클러스터 파일 시스템을 통하여 응용 프로그램에 대한 단일 입출력공간을 제공하고 효율적인 파일/디렉토리 연산을 제공하는 기술이 중요하다. 본 논문에서는 리눅스 클러스터 시스템을 위한 클러스터 파일 시스템(Cluster File System, 이하 CFS로 표기)을 설계 및 구현한다. CFS는 리눅스 파일 시스템 위에 사용자 수준에서 구현된 시스템으로 사용자에게는 단일 시스템 이미지를 제공한다. 내부적으로는 대용량의 파일이 분산되어 저장되며 이를 위해 파일/디렉토리 정보도 각각의 노드에서 분산 관리된다. 사용자에게는 응용 프로그램의 개발이 용이하도록 API가 제공되며, 또한 CFS를 관리하기 위한 도구들이 제공된다.

• Annual Conference of KIPS
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• 2016.04a
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• pp.142-145
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• 2016

본 논문은 기존의 RFID 감지 시스템에서 더 나아가 다수의 RFID 클러스터의 협업 및 RFID가 부착된 객체들 사이의 관계를 통하여 객체 추적이 가능한 시스템을 제안한다. 서버는 다수 클러스터와의 통신으로 모든 객체의 데이터를 관리하며 클러스터는 객체의 RFID가 감지되는 경우에 객체의 데이터를 얻어 서버에 전송한다. 이러한 서버와 클러스터의 상호작용을 통해 감지된 클러스터의 위치를 파악하여 객체 추적이 가능하다. 만약 RFID를 감지하는 데 있어 문제가 발생할 경우, 객체 관계를 활용하여 해결한다. 얻은 데이터의 신뢰도가 낮더라도 RFID가 감지된 상황에 따라 가진 데이터를 기반으로 객체는 싱글과 그룹 관계로 결정되며 시간이 지남에 따라 그룹 관계를 싱글 관계로 바꾸어 모든 객체를 분별할 수 있도록 한다. 실제 제한된 실내 공간을 선정해 이를 기반으로 시뮬레이션 프로그램을 구현하여 이 시스템의 효율성을 확인하였다.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.1
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• pp.19-43
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• 2007

The purpose of this study is to distinguish industrial clusters in Korea. Based on I/O table in 2000, coefficient matrix was calculated and factor analysis was performed on the matrix. Among 38 derived industrial clusters, 5 of them were unreported clusters, which were indistinguishable. Once these 38 industrial clusters were differentiated according to I/O table, final results of clusters were produced as I/O table was converted into KSIC (Korean Standard Industry Code). Since existing studies on industrial cluster have been focused on qualitative methods such as case studies and interviews, it is expected that this study could contribute to carry out more systematic and efficient methodology.

• Journal of the Korean Geographical Society
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• v.44 no.5
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• pp.634-646
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• 2009

This paper critically examines cluster dynamics and development in a multi-scalar approach, criticizing both the argument overemphasizing local networks and endogenous development for regional development and the contention highlighting global networks and the role of global players. We argue that state policies, exogenous and direct, play a significant part in cluster dynamics and development especially in the case of Korea where the state government's strong policies have led to rapid industrialization. We analyze multi-scalar factors, especially the government policies at a national level, in the development paths of the three cases including Ulsan automobile cluster, Daedeok research cluster, and Dongdaemun fashion cluster.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.277-284
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• 2004

This paper presents a facial expression control method of 3D avatar that enables the user to select a sequence of facial frames from the facial expression space, whose level of details the user can select hierarchically. Our system creates the facial expression spare from about 2,400 captured facial frames. But because there are too many facial expressions to select from, the user faces difficulty in navigating the space. So, we visualize the space hierarchically. To partition the space into a hierarchy of subspaces, we use fuzzy clustering. In the beginning, the system creates about 11 clusters from the space of 2,400 facial expressions. The cluster centers are displayed on 2D screen and are used as candidate key frames for key frame animation. When the user zooms in (zoom is discrete), it means that the user wants to see mort details. So, the system creates more clusters for the new level of zoom-in. Every time the level of zoom-in increases, the system doubles the number of clusters. The user selects new key frames along the navigation path of the previous level. At the maximum zoom-in, the user completes facial expression control specification. At the maximum, the user can go back to previous level by zooming out, and update the navigation path. We let users use the system to control facial expression of 3D avatar, and evaluate the system based on the results.

• The Journal of Society for e-Business Studies
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• v.8 no.4
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• pp.69-88
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• 2003

In high dimensional data, most of clustering algorithms tend to degrade the performance rapidly because of nature of sparsity and amount of noise. Recently, partial dimensional clustering algorithms have been studied, which have good performance in clustering. These algorithms select the dimensional data closely related to clustering but discard the dimensional data which are not directly related to clustering in entire dimensional data. However, the traditional algorithms have some problems. At first, the algorithms employ grid based techniques but the large amount of grids make worse the performance of algorithm in terms of computational time and memory space. Secondly, the algorithms explore dimensions related to clustering using k-medoid but it is very difficult to determine the best quality of k-medoids in large amount of high dimensional data. In this paper, we propose an efficient partial dimensional clustering algorithm which is called CLIP. CLIP explores dense regions for cluster on a certain dimension. Then, the algorithm probes dense regions on a next dimension. dependent on the dense regions of the explored dimension using incremental projection. CLIP repeats these probing work in all dimensions. Clustering by Incremental projection can prune the search space largely and reduce the computational time considerably. We evaluate the performance(efficiency, effectiveness and accuracy, etc.) of the proposed algorithm compared with other algorithms using common synthetic data.

• The KIPS Transactions:PartA
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• v.13A no.7 s.104
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• pp.607-614
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• 2006

The checkpointing schemes should reduce the process delay through managing the checkpoints of each node to fit the network load to enhance the performance of the process running on the cluster system that write the checkpoints into its global stable storage. For this reason, a cluster system with single IO space on a distributed RAID chooses a suitable checkpointng scheme to get the maximum IO performance and the best rollback recovery efficiency. In this paper, we improved the striped checkpointing scheme with dynamic stripe group size by adapting to the network bandwidth variation at the point of checkpointing. To analyze the performance of the multi striped checkpointing scheme, we applied Linpack HPC benchmark with MPI on our own cluster system with maximum 512 virtual nodes. The benchmark results showed that the multistriped checkpointing scheme has better performance than the striped checkpointing scheme on the checkpoint writing efficiency and rollback recovery at heavy system load.

• The KIPS Transactions:PartA
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• v.13A no.6 s.103
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• pp.517-524
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• 2006

In cluster computers, it is essential to Implement the single I/O space(SIOS) supporting integrated I/O substructure to efficiently process I/O intensive applications. SIOS service provides with global I/O address space to directly access peripherals and hard disks in its own or remote nodes from any node in the cluster computer In this thesis, we propose the implementation method of SIOS in Linux clusters by using only freewares. This method is implemented at device driver level that uses Enhanced Network Block Device(ENBD) and file system level that uses S/W RAID and NFS. The major strengths of this method are easiness of implementation and almost no cost due to using freewares. In addition, since freewares used are open sources, it is possible to apply this method to other platforms with only slight modification. Moreover, experiments show that I/O throughputs are up to 5.5 times higher in write operations and approximately 2.3 times higher in read operations than those of CDD method that uses the device driver developed at kernel level.