• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2003년도 춘계학술대회논문집
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• pp.67-71
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• 2003

In order to manage a cluster system that consists of a number servers, management aspects such as configuration management, fault management, performance management, and user management should be considered. Especially, it is necessary to monitor performances for performance and fault management. An agent in each server collects performance counters, status changes, and events occurred in normal or abnormal states. The data collected are delivered to a collector sorter and processed in a report tool for performance analysts and management decision in the cluster system point of view, by detecting fault state and tracing out resource usage, service response, and response, and states until failed. In this paper we propose an architecture modeling of a performance report tool for proactive cluster system management. Some results on a cluster system are presented.

• 한국정보시스템학회지:정보시스템연구
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• 제17권3호
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• pp.135-152
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• 2008

Basically within a special regional area, a regional cluster seems to be based on core competencies of individual intra-cluster companies and collaboration among them. Information infrastructure has been emphasized as on one of competitive factors of a regional cluster, and it can be organized using collaboration system architecture integrated with each company's internal systems for efficient supply chain operation. As one of technical methods to prepare the system infrastructure supporting the collaboration of companies in a regional cluster, the Web Services can be effectively used. In this paper, a collaborative information system infrastructure for a regional cluster is suggested within the scope of supply chain management. And the efficiency of the proposed alternative is appraised with the features of a regional cluster.

• 디지털산업정보학회논문지
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• 제16권2호
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• pp.11-25
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• 2020

This study proposes a method to manipulate fragmentation of disks by arbitrarily allocating and releasing the status of a disk cluster in the NTFS file system. This method allows experiments to be performed in several studies related to fragmentation problems on disk cluster. Typical applicable research examples include testing the performance of disk defragmentation tools according to the state of fragmentation, establishing an experimental environment for fragmented file carving methods for digital forensics, setting up cluster fragmentation for testing the robustness of data hiding methods within directory indexes, and testing the file system's disk allocation methods according to the various version of Windows. This method suggests how a single file occupies a cluster and presents an algorithm with a flowchart. It raises three tricky problems to solve the method, and we propose solutions to the problems. Experiments for allocating the disk cluster to be fragmented to the maximum extent possible, it then performs a disk defragmentation experiment to prove the proposed method is effective.

• Journal of Information Technology Applications and Management
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• 제12권3호
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• pp.41-56
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• 2005

Product recommender system is one of the most popular techniques for customer relationship management. In addition, collaborative filtering (CF) has been known to be one of the most successful recommendation techniques in product recommender systems. However, CF has some limitations such as sparsity and scalability problems. This study proposes hybrid cluster analysis and case-based reasoning (CBR) to address these problems. CBR may relieve the sparsity problem because it recommends products using customer profile and transaction data, but it may still give rise to scalability problem. Thus, this study uses cluster analysis to reduce search space prior to CBR for scalability Problem. For cluster analysis, this study employs hybrid genetic and K-Means algorithms to avoid possibility of convergence in local minima of typical cluster analyses. This study also develops a Web-based prototype system to test the superiority of the proposed model.

• 디지털산업정보학회논문지
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• 제13권2호
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• pp.77-85
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• 2017

Due to the expansion of accommodation space caused by increase of population along with lifestyle changes, most of people spend their time indoor except for the travel time. Because of this, environmental change of indoor is very important, and it affects people's health and economy in resources. But, most of people don't acknowledge the importance of indoor environment. Thus, monitoring system for sustaining and managing indoor environment systematically is needed, and big data clusters should be used in order to save and manage numerous sensor data collected from many spaces. In this paper, we design a big data cluster for the indoor environment monitoring in order to store the sensor data and monitor unit of the huge building Implementation design big data cluster-based system for the analysis, and a distributed file system and building a Hadoop, HBase for big data processing. Also, various sensor data is saved for collection, and effective indoor environment management and health enhancement through monitoring is expected.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.134-140
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• 2023

The distributed system is playing a vital role in storing and processing big data and data generation is speedily increasing from various sources every second. Hadoop has a scalable, and efficient distributed system supporting commodity hardware by combining different networks in the topographical locality. Node support in the Hadoop cluster is rapidly increasing in different versions which are facing difficulty to manage clusters. Hadoop does not provide Node management, adding and deletion node futures. Node identification in a cluster completely depends on DHCP servers which managing IP addresses, hostname based on the physical address (MAC) address of each Node. There is a scope to the hacker to theft the data using IP or Hostname and creating a disturbance in a distributed system by adding a malicious node, assigning duplicate IP. This paper proposing novel node management for the distributed system using DNA hiding and generating a unique key using a unique physical address (MAC) of each node and hostname. The proposed mechanism is providing better node management for the Hadoop cluster providing adding and deletion node mechanism by using limited computations and providing better node security from hackers. The main target of this paper is to propose an algorithm to implement Node information hiding in DNA sequences to increase and provide security to the node from hackers.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제8권6호
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• pp.639-646
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• 2002

본 논문에서는 리눅스 클러스터 시스템 통합 관리 도구인 CATS-i'(Cluster Administration ToolS on the Internet)의 시스템 구성과 디자인 문제들을 논한다. CATS-i'는 리눅스 클러스터 시스템을 쉽고 빠르고 안전하게 설치하고 관리하기 위하여 개발된 도구이다. 클러스터의 운영체제 설치에서부터 응용 프로그램 패키지 설치, 클러스터 노드들의 자원들을 실시간으로 모니터링하고 관리할 수 있는 기능, 배치 작업 제출 및 관리 기능들이 통합되어 사용자에게 단일 시스템 이미지를 제공한다. 또한 사용자가 플랫폼에 관계없이 쉽고 편리하게 클러스터의 상태를 파악하고 관리할 수 있는 자바 기반의 강력한 그래픽 사용자 인터페이스를 제공한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 추계학술대회
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• pp.435-437
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• 2016

하둡 분산 파일시스템(HDFS)는 빅데이터의 병렬 분산 처리를 위해 다수의 노드에 데이터를 중복 저장하는 파일시스템이다. HDFS의 분산 노드 클러스터는 수천 개 이상의 규모 확장성을 갖추고 있으나 빅데이터 처리를 위한 전용 하드웨어를 가정하고 있으며, 기존의 기업 및 병원에서 사용하고 있는 다양한 유휴 전산 자원을 고려하지는 못하는 문제가 있다. 본 논문에서는 기관 내 존재하는 다양한 유휴 전산 자원을 필요에 따라 동적으로 HDFS에 추가함으로써 빅데이터 저장 및 분석 성능을 향상시킬 수 있는 동적 클러스터 관리 기법을 제시한다.

• 한국산림과학회지
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• 제95권3호
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• pp.370-377
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• 2006

본 연구는 지속가능한 산림경영에 적합한 표본조사 방법을 제시하기 위해 계통적 추출법, 계통적 집락추출법, 그리고 층화집락추출법을 이용하여 경기도 양평군의 산림을 대상으로 자료를 수집한 후 통계검증을 실시하였다. 표본조사 방법은 계통적 집락추출법이 가장 효율적인 것으로 분석되었는데, 계통적 집락추출법을 적용할 경우 집락의 형태와 집락 내의 표본점 간의 거리를 결정하기 위해 5가지 집락의 형태와 표본점간의 거리 4가지에 대하여 통계검증을 실시하였다. 그 결과 집락의 형태는 삼각형 그리고 집락 내의 표본점 간의 거리는 50m가 가장 적합할 것으로 평가되었다.

• 대기
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• 제15권1호
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• pp.35-46
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• 2005

Today, the outreach of National Meteorological Service such as PC cluster based Numerical Weather Prediction (NWP) technique is vigorous in the world wide. In this regard, WMO (World Meteorological Organization) asked KMA (Korea Meteorological Administration) to formulate a regional project, which cover most of RA II members, using similar technical system with KMA's. In that sense, Meteorological Research Institute (METRI) in KMA developed Mongolian NWP System (MNWPS) based on PC cluster and transferred the technology to Weather Service Center in Mongolia. The hybrid parallel algorithm and channel bonding technique were adopted to cut cost and showed 41% faster performance than single MPI (Message Passing Interface) approach. The cluster technique of Beowulf type was also adopted for convenient management and saving resources. The Linux based free operating system provide very cost effective solution for operating multi-nodes. Additionally, the GNU software provide many tools, utilities and applications for construction and management of a cluster. A flash flood event happened in Mongolia (2 September 2003) was selected for test run, and MNWPS successfully simulated the event with initial and boundary condition from Global Data Assimilation and Prediction System (GDAPS) of KMA. Now, the cluster based NWP System in Mongolia has been operated for local prediction around the region and provided various auxiliary charts.