• Journal of KIISE:Databases
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• v.35 no.5
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• pp.400-410
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• 2008

Flash memory has been widely used in mobile devices, such as mobile phone and digital camera. Recently flash SSD(Solid State Disk), having same interface of the disk drive, is replacing the hard disk of some laptop computers. However, flash memory still cannot be considered as the storage of database systems. The FTL(Flash Translation Layer) of commercial flash SSD, making flash memory operate exactly same as a hard disk, shows poor performance on the workload of databases with many random overwrites. Recently In-Page Logging(IPL) approach was proposed to solve this problem. In this paper, we implement IPL approach on SQLite, a popular open source embedded DBMS, and evaluate its performance. It improves the performance by up to 30 factors for update queries.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.32-43
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• 2013

These days, there are more and more IT research institutions which foresee cloud services as the predominant IT service in the near future and there, in fact, are actual cloud services provided by some IT leading vendors. Regardless of physical location of the service and environment of the system, cloud service can provide users with storage services, usage of data and software. On the other hand, cloud service has challenges as well. Even though cloud service has its edge in terms of the extent to which the IT resource can be freely utilized regardless of the confinement of hardware, the availability is another problem to be solved. Hence, this paper is dedicated to tackle the aforementioned issues; prerequisites of cloud computing for distributed file system, open source based Hadoop distributed file system, in-memory database technology and high availability database system. Also the author tries to body out the high availability mass distributed data management architecture in cloud service's perspective using currently used distributed file system in cloud computing market.

• KIISE Transactions on Computing Practices
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• v.21 no.8
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• pp.537-542
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• 2015

Database Shard is a technique that can be queried and stored by dividing one logical table into multiple databases horizontally. In order to analyze the shard data with aggregate or analysis functions, a process is required that integrates partial results on each shard database. In this paper, we introduce the design and implementation of a distributed processing system for aggregation and analysis on the CUBRID Shard distributed database, which is an open source database management system. The implemented system can accelerate the analysis onto multiple shards of partitioned tables; it shows efficient aggregation on shard distributed databases compared to stand-alone databases.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.689-698
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• 2009

SOLAP system integrates and complements the functions of both OLAP and GIS systems. This enables users not only to easily access geospatial data but also to analyze and extract information for decision making. In this study a SOLAP system was designed and implemented to provide urban planners with GIS information when making urban planning decisions. Rapid urbanization in Korea has brought about ill-balanced urban structure as the result of development without detailed analysis of urban plans. Systematic urban planning procedures and automated systems are crucial for detail analysis of future development plans. Data regarding the development regulations and current status of land use need to be assessed precisely and instantly. Multi-dimensional aspects of a suggested plan must be formulated instantly and examined thoroughly using 'what if' scenarios to come up with a best possible plan. The SOLAP system presented in this study designed the dimension tables and the fact tables for supplying timely geospatial information to the planners when making decisions regarding urban planning. The database was implemented using open source DBMS and was populated with necessary attribute data which was freely available from the Statistics Korea bureau homepage. It is anticipated the SOLAP system presented in this study will contribute to better urban planning decisions in Korea through more timely and accurate provision of geospatial information.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.133-142
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• 2010

As diverse web-based geos-spatial services are developed, the values of technologies and standards related to this trend are also emphasized. In this study, a prototype supporting mandatory components in OGC standard catalog service is designed and implemented, linked to PostgreSQL, open source DBMS. As the main features, XML metadata server was built with the helps of XML query functions in PostgreSQL. Given target applications with geo-spatial data sources and contents, this model can be applied, and it can be used for extension in other external web-based service systems or applications, because it supports international standard specifications.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.349-354
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• 2014

Since Hadoop which is the Big-data processing platform was announced, SQL-on-Hadoop is the spotlight as the technique to analyze data using SQL on Hadoop. Tajo created by Korean programmers has recently been promoted to Top-Level-Project status by the Apache in April and has been paid attention all around world. Despite a sensible change caused by Hadoop's appearance in DW market, researches of those performance is insufficient. Thus, this study has been conducted to help choose a DW solution based on SQL-on-Hadoop as progressing the test on comparison analysis of RDBMS and Tajo. It has shown that Tajo based on Hadoop is more superior than RDBMS if it is used with accurate strategy. In addition, open-source project Tajo is expected not only to achieve improvements in technique due to active participation of many developers but also to be in charge of an important role of DW in the filed of data analysis.

• 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.