• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.164-168
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• 2023

There are many possible ways to configure database management systems (DBMSs) have challenging to manage and set.The problem increased in large-scale deployments with thousands or millions of individual DBMS that each have their setting requirements. Recent research has explored using machine learning-based (ML) agents to overcome this problem's automated tuning of DBMSs. These agents extract performance metrics and behavioral information from the DBMS and then train models with this data to select tuning actions that they predict will have the most benefit. This paper discusses two engineering approaches for integrating ML agents in a DBMS. The first is to build an external tuning controller that treats the DBMS as a black box. The second is to incorporate the ML agents natively in the DBMS's architecture.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.115-121
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• 2024

Each ADS must have a validation and evaluation scenario for ODD. This requires a large number of scenarios, so a scenario library must be developed. In order to effectively utilize the scenario library, a system that supports testing in the ODD of the user's choice is required. In other words, in order to develop a scenario library, it is necessary to build a database on actual driving road conditions (geometry, etc.). Accordingly, in this study, we establish a domestic driving environment database based on HD-Map for driving safety testing, design a system that can search test target sections in connection with the ODD of the scenario, and present the implementation results. In the future, it is expected that the domestic driving environment database will be able to create scenarios through linking with the scenario library and directly utilize them for scenario-based evaluation of various demand sources.

• Proceedings of the Korea Association of Information Systems Conference
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• 2000.11a
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• pp.25-35
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• 2000

A huge amount of financial information in large databases makes performance comparisons among organizations difficult or at least very time-consuming. This paper investigates whether neural networks in the form of self-organizing maps can be effectively employed to perform a competitive benchmarking in large databases. By using self-organizing maps, we expect to overcome problems associated with finding appropriate underlying distributions and functional forms of underlying data. The method also offers a way of visualizing the results. The database in this study consists of annual financial reports of 100 biggest Korean companies over the years 1998, 1999, and 2000.

• Spatial Information Research
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• v.13 no.3 s.34
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• pp.221-237
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• 2005

This study attempts at building a GIS computing environment that incorporates object-relational spatio-temporal database for the time geography model with space-time path, space-time prism and space-time accessibility. The proposed computing environment is composed of ( i ) mobile GIS application for collecting spatio-temporal trajectory data of an individual, ( ii ) spatio-temporal database server that includes time geography model, and (iii) geovisualization client that performs time geographic queries to the spatio-temporal database. The spatio-temporal trajectory data collected by GPS-PDA client is automatically processed and sent to server through data management middleware. The spatio-temporal database implemented by extending a generic DBMS provides spatio-temporal objects, functions, and SQL. The geovisualization client illustrates 3D visual results of the queries about space-time path, space-time prism, and space-time accessibility. This study confirms the possibility of integrating mobile GIS and DBMS for time geography model, and it presents the appropriate database model with spatio-temporal objects and functions that may handle very large data for time geography application.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.1-9
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• 2020

In this paper, we propose a method of in-depth analysis of internal operation process by recording library calls and related information that occur in the operation process of NoSQL database. It observes and records the specified library calls, compares the internal behavior differences between the NoSQL databases through recorded library call information, and evaluates the characteristics and scalability of each database by observing changes in the number of input data. The development of computing performance and the activation of big data have led to the emergence of different types of NoSQL databases for recording and analyzing various and large amounts of data, and it is necessary to evaluate the scalability of each database in order to select a database suitable for each environment. However, it is difficult to analyze or predict how a database operates in traditional ways, such as benchmarking, observing external behavior through performance models, or analyzing structural features based on design. Therefore, it is necessary to utilize the techniques proposed in this paper to understand the scalability of NoSQL databases with high accuracy.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.8
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• pp.758-762
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• 2008

Embedded systems usually utilize Flash Memories with very nice characteristics of non-volatility, low access time, low power and so on. For the multimedia database systems, R-tree is an indexing tree with nice characteristics for multimedia access. MR-tree, which is an upgraded version of R-tree, has shown better performance in searching, inserting and deleting operations than R-tree. Flash memory has sectors and blocks as a unit of read, write and delete operations. Especially, the delete is done on a unit of 512 byte blocks with very large operation time and it is also known that read and write operations on a unit of block matches caching nature of MT-tree. Our research optimizes MR-tree operations in a unit of Flash memory blocks. Such an adjusting leads in better indexing performance in database accesses. With MR-tree on a 512B block units we achieved fast search time of database indexing with low height of MR-tree as well as faster update time of database indexing with the best fit of flash memory blocks. Thus MR-tree with optimized operations shows good characteristics to be a database index schemes on any systems with flash memory.

• The Journal of Natural Sciences
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• v.5 no.2
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• pp.25-32
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• 1992

Statistical database(SDB) are large database primarily collected for purpose of statistical analysis. Commerical database management systems have not been widely used for SDB because of the efficiency problem of storage and access of those systems for SDB. In this paper, we propose SDB management method to use a front-end system to a Relatianal Datebase Management System (RDBMS). We do the design of SM-F system (Stasticical database Management as Front-end system) as a front-end system to a RDBMS. In the system, we use GROS model specially proposed for SDB, and store and manage summary database and meta database to support statistical analysis and to provide users with statistical summary information.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.1867-1879
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• 1997

DREAM-S is a distributed main-memory database system for the real-time processing of shared operational datra in ATM switching systems. DREAM-S has a client-server architecture in which only the server has the diskstorage, and provides the T-Tree index structure for efficient accesses to the data. We propose a recovery technique for the T-Tree index structre in DREAM-S. Although main-memory database system offer efficient access performance, the database int he main-memory may be broken when system failure such as database transaction failure or power failure occurs. Therfore, a recovery technique that recovers the database (including index structures) is essential for fault tolerant ATM switching systems. Proposed recovery technique relieves the bottleneck of the server processors disk operations by maintaining the T-Tree index structure only in the main-memory. In addition, fast recovery is guaranteed even in large number of client systems since the T-Tree index structure(s) in each system can be recovered cncurrently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.333-338
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• 2017

Recently, because of the mobile device generalization tendency, a lot of new mobile applications which need mobile database on mobile devices appear. SQLite, Realm, etc. are representative mobile databases, and they are the database engines which are suitable for small devices that have large resource restriction and are used a lot in mobile devices based on Linux. These engines are open source programs and have advantages which are lighter weight and faster speed than general purpose databases. This paper focuses on the performance experiments and analysis of SQLite, which is front runner in mobile database fields. Considering the target mobile environments, the test is performed at Linux environment. And this paper implements performance test program and performs performance experiment of SQLite database to test search efficiency. The experiment is processed by comparison with the results of a Oracle database working out at the same environment.

• Journal of Information Technology Services
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• v.21 no.4
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• pp.63-74
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• 2022

Globally researchers at medical institutions are actively sharing COHORT data of patients to develop vaccines and treatments to overcome the COVID-19 crisis. OMOP-CDM, a common data model that efficiently shares medical data research independently operated by individual medical institutions has patient personal information (e.g. PII, PHI). Although PII and PHI are managed and shared indistinguishably through de-identification or anonymization in medical institutions they could not be guaranteed at 100% by complete de-identification and anonymization. For this reason the security of the OMOP-CDM database is important but there is no detailed and specific OMOP-CDM security inspection tool so risk mitigation measures are being taken with a general security inspection tool. This study intends to study and present a model for implementing a tool to check the security vulnerability of OMOP-CDM by analyzing the security guidelines for the US database and security controls of the personal information protection of the NIST. Additionally it intends to verify the implementation feasibility by real field demonstration in an actual 3 hospitals environment. As a result of checking the security status of the test server and the CDM database of the three hospitals in operation, most of the database audit and encryption functions were found to be insufficient. Based on these inspection results it was applied to the optimization study of the complex and time-consuming CDM CSF developed in the "Development of Security Framework Required for CDM-based Distributed Research" task of the Korea Health Industry Promotion Agency. According to several recent newspaper articles, Ramsomware attacks on financially large hospitals are intensifying. Organizations that are currently operating or will operate CDM databases need to install database audits(proofing) and encryption (data protection) that are not provided by the OMOP-CDM database template to prevent attackers from compromising.