• 한국공간정보시스템학회:학술대회논문집
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• 2000.06a
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• pp.23-34
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• 2000

최근 네트웍의 보급과 지리정보의 활용이 증가하면서 효과적인 지리정보의 교환과 접근에 대한 중요성이 강조되고 있다. 하지만 기존의 GIS 데이터는 지리적으로 분리된 여러 부서나 조직에서 생성되고 있으며, 공간 정보 유통을 위한 클리어링하우스 등이 서로 다른 DBMS 상에서 독자적인 스키마를 가지고 개발되어 있다. 이러한 이질적인 구조와 구현 환경으로 인해 일반 사용자들이 서로 다른 GIS 데이터베이스를 접근하여 검색하는데 많은 어려움이 따르고 있다. 본 연구에서는 OMG의 메타데이터 교환 표준인 XMI로 표현된 이질적인 GIS 데이터베이스의 메타데이터를 통하여 사용자에게 각 데이터베이스의 구현 환경과 스키마에 독립적인 공간 데이터를 검색 기능을 제공하는 검색시스템을 구현하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.151-153
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• 2005

유비쿼터스 연구가 진행되면서 서로 데이터 모델이 안지 않는 이기종 데이터베이스 간의 데이터 교환이 중요한 문제로 대두되었다. XML문서는 데이터 호환성이 뛰어나 유비쿼터스 환경에 맞는 데이터 교환 수단으로 적합하다. 데이터베이스 시스템의 장점때문에 XML 문서를 객체 관계 데이터베이스에 저장하는 연구가 진행되었다. 객체 관계 데이터베이스 시스템에 XML 문서를 저장하고 질의하는 방법에는 여러 가지가 있다. 이 논문에서는 분산 환경에서 객체 관계 데이터베이스 시스템에 XML 문서를 저장하고 질의하는 방법을 논의하고, 성능 평가를 수행한다.

• Water Engineering Research
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• v.3 no.2
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• pp.85-92
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• 2002

There has been continuous efforts to manage water resources for the required water quality criterion at river channel in Korea. However, we could obtain the partial improvement only for the point sources such as, waste waters from urban and factory site through the water quality management. Therefore, it is strongly needed that the best management practice throughout the river basin fur water quality management including non-point sources pollutant loads. This problem should be resolved by recognizing the non-point sources pollutant loads from the upstream river basin to the outlet of the basin depends on the landuse and soil type characteristics of the river basin using the computer simulation by a distributed model based on the detailed investigation and application of Geographic Information System (GIS). The purpose of this study is consisted of the three major distributions, which are the investigation of spread non-point sources pollutants throughout the river basin, development of the base maps to represent and interpret the input and outputs of the distributed simulation model, and prediction of non-point sources pollutant loads at the outlet of a up-stream river basin using Agricultural Non-Point Sources Model (AGNPS). For the validation purpose, the Seom-Jin River basin was selected with two flood events in 1998. The results of this application showed that the use of combined a distributed model and an application of GIS was very effective fur the best water resources and quality management practice throughout the river basin

• Journal of Korea Multimedia Society
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• v.7 no.9
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• pp.1329-1338
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• 2004

The purpose of data mining is to extract multi-dimensional information from a large database. The only information that we can extract from a large database is the column name, data type or simple comments included in the columns of database tables. With such unstructured and scarce information, it is very difficult and time taking to collect and to cleanse data by analyzing the purpose, characteristic and schema of the column during the data preparation step. In order to solve this problem, we propose solutions for reducing the time spent data preparation step in a relational database environment in this paper. That is, we propose useful elements to be considered during the data preparation step and then these elements are organized to constitute MDR(Metadata Registry) which is becoming the international standard of ISO/IEC : ll179. Finally, we propose a XML-based distributed MDR retrieval system that is convertible among heterogeneous systems and heterogeneous DBMSS.

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.2
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• pp.65-72
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• 1993

When a drought occurs in an area irrigated by multi-reservoirs, onerating a single reservoir separately to control the reservoir' storage is not a desirable solution. In order to reduce damages effectively for the areal drought, the storage of the reservoirs within the areal boundary should be managed as a group. Storage management procedures are as follows : 1. Collecting and checking the present storages of all reservoirs 2. Computing the drought frequency and depth; and finally, establishing a suitable storage saving strategy based on the estimated drought depth. For the purpose of this storage management, the RESTOMS(Reservoirs Storage Management System) was developed and the system was composed of the PRIME computer and the ORACLE as a distributed database management system, which was the host computer of Rural Development Corporation and would be on-lined with the regional offices throughout the country. Reservoirs operated by Farm Land Improvment Association were comprised in the DB system. Using the RESTOMS, the drought frequencies and drought depths were calculated with respect to the reservoir storage records(1967 to 1992). It was obvious that the results were closely corresponding to the real drought records.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.574-576
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• 2021

It is necessary to introduce micro-service techniques when constructing large-scale operating systems or systems that take into account scalability. Kafka is a message queue with the pub/sub model, which has features that are well applied to distributed environments and is also suitable for microservices in that it can utilize various data sources. In this paper, we propose a data sharing method for educational video sharing services using Apache's Kafka. The proposed system builds a Kafka cluster for the educational video sharing service to share various data, and also uses a spark cluster to link with recommendation systems based on similarities in educational videos. We also present a way to share various data sources, such as files, various DBMS, etc.

• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.12-26
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• 2004

In the past, geographic data is constructed and serviced through independent formats of its own according to each GIS(Geographic Information System). Recently the provision of interoperability in GIS is important to efficiently apply the various geographic data between conventional GIS's. Whereupon OGC(Open GIS Consortium) proposed GML(Geography Markup Language) to offer the interoperability between heterogeneous GISs in distributed environments. The GML is an XML encoding for the transport and storage of geographic information, including both the spatial and non-spatial properties of geographic features. Also, the GML includes Web Map Server Implementation Specification to service the GML documents. Accordingly the prototype to provide the reciprocal interchange of geographic information between conventional GIS's and GML documents is widely studied. In this paper, we propose a mapping method of geographic in formation between spatial database and GML for the prototype to support the interoperability between heterogeneous geographic information. For this method, firstly the scheme of converting geographic in Formation of the conventional spatial database into the GML document according to the GML specification is explained, and secondly the scheme to transform geographic information of GML documents to geographic data of spatial database is showed. Consequently, the proposed method is applicable to the framework for integrated geographic information services based on Web by making an offer the interoperability between already built geographic information of conventional GIS's using a mapping method of geographic information between spatial database and GML.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.26-35
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• 2011

In these days, internet environment are very quickly development as well on-line service have been using a online for the mission critical business around the world. As the amount of information to be processed by computers has recently been increased there has been cluster computing systems developed by connecting workstations server using high speed networks for high availability. but cluster computing technology are limited for a lot of IT resources. So, grid computing is an expanded technology of distributed computing technology to use low-cost and high-performance computing power in various fields. Although the purpose of Grid computing focuses on large-scale resource sharing, innovative applications, and in some case, high-performance orientation, it has been used as conventional distributed computing environment like clustered computer until now because grid middleware does not have common sharable information system. In order to use grid computing environment efficiently which consists of various grid middleware, it is necessary to have application-independent information system which can share information description and services, and expand them easily. This paper proposed new database architecture and load balancing for high availability through Grid technology.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.570-581
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• 2015

In recent years, many institutions predict that cloud services and big data will be popular IT trends in the near future. A number of leading IT vendors are focusing on practical solutions and services for cloud and big data. In addition, cloud has the advantage of unrestricted in selecting resources for business model based on a variety of internet-based technologies which is the reason that provisioning and virtualization technologies for active resource expansion has been attracting attention as a leading technology above all the other technologies. Big data took data prediction model to another level by providing the base for the analysis of unstructured data that could not have been analyzed in the past. Since what cloud services and big data have in common is the services and analysis based on mass amount of data, efficient operation and designing of mass data has become a critical issue from the early stage of development. Thus, in this paper, I would like to establish data processing architecture based on technological requirements of mass data for cloud and big data services. Particularly, I would like to introduce requirements that must be met in order for distributed file system to engage in cloud computing, and efficient compression technology requirements of mass data for big data and cloud computing in terms of cost-saving, as well as technological requirements of open-source-based system such as Hadoop eco system distributed file system and memory database that are available in cloud computing.