• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.139-142
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• 2008

While a lot of comparisons of DBMS performance for processing large scale database are given as results of bench-mark tests, there are few comparisons of DBMS performance for processing small scale database. Therefore, in this study, we compared and analyzed on the performance of commercial DBMS and public DBMS for small scale database. Analysis results show that while Oracle has low performance on the operations of update and insert due to the overhead of rollback for data safety, MySQL and MS-SQL have good performance without additional overhead.

• Journal of KIISE
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• v.43 no.12
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• pp.1385-1395
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• 2016

In the era of Big Data, NoSQL databases provide solutions for problems, circumventing the limitations of traditional relational databases by using new architectures and data model. Contrary to relational database products, the range of the features architectures, and limitations of NoSQL databases is very broad. Thus, choosing the right database products requires more considerations and difficulties. The advent of NoSQL does not only promote the abundance of NoSQL products, but also stimulates the relational database realm to expand their features beyond the relational model. In order to understand NoSQL trends more accurately, here we discuss and compare NoSQL databases with relational databases. We also present the newest features associated with NoSQL in one of the most advanced open-source relational databases, PostgreSQL. To discuss future directions for PostgreSQL we analyzed the performance of NoSQL and PostgreSQL by conducting experiments using the NoSQL benchmark tool (YCSB).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.1999-2004
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• 2008

While a lot of comparisons of DBMS performance for processing large scale database are given as results of bench-mark tests, there are few comparisons of DBMS performance for processing small scale database. Therefore, in this study, we compared and analyzed on the performance of commercial DBMS and public DBMS for small scale database. Analysis results show that while Oracle has low performance on the operations of update and insert due to the overhead of rollback for data safely, MySQL and MS-SOL have good performance without additional overhead.

• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.390-394
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• 2010

본 논문에서는 영상인식에서 널리 사용되는 지역적 특징인 SIFT와 부분공간분석에 의한 차원축소방법의 결합을 통하여 얼굴을 인식하는 방법을 제안한다. 기존의 SIFT기반 영상인식 방법에서는 추출된 키 포인트 각각에 대하여 계산된 특징기술자들을 개별적으로 비교하여 얻어지는 유사도를 바탕으로 인식을 수행하는데 반해, 본 논문에서 제안하는 접근법은 SIFT의 특징기술자를 명도 값으로 표현된 얼굴 영상을 여려 변형에 강건한 형태로 표현되도록 변환하는 표현방식으로 본다. SIFT기반의 특징기술자에 의해 표현된 얼굴 영상을 부분공간분석법에 의해 저차원의 특징벡터로 다시 표현되고, 이 특징벡터를 이용하여 얼굴인식을 수행한다. 잘 알려진 벤치마크 데이터인 AR 데이터베이스에 대한 실험을 통해 제안한 방법이 조명 변화와 가려짐에 강인한 인식 결과를 보여줄 뿐 아니라, 기존의 SIFT 기반의 얼굴 인식 방법에 비하여 우수한 처리 속도를 보임을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.71-72
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• 2013

최근 연구 개발되고 있는 스토리지 클래스 메모리는 정체되어 있는 스토리지와 DRAM 산업에 큰 변화를 가져올 것으로 예상된다. 현재 컴퓨팅 환경에서 스토리지의 성능 저하요소가 큰 이슈로 야기되어지는 가운데 본 논문에서는 TPC-C 벤치마크를 이용하여 임의 쓰기와 덮어 쓰기 연산 시 발생되는 문제점들을 분석한다. 실험 결과를 통해 향후 스토리지 클래스 메모리를 활용하여 기존 쓰기 연산 시 발행 하는 문제점들을 해결할 수 있는 방안에 대해 논의 한다.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.5
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• pp.121-128
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• 2002

Although multiprocessor systems are widely used in recent years to run commercial workloads, data sharing patterns are rarely explored due to several difficulties. In this paper, we made in-depth sharing pattern analysis for a representative OLTP application, the TPC-B benchmark, running on a cache-coherent shared-memory multiprocessor system. In addition, to illustrate their effects on the performance, the number of cache misses were measured for various numbers of processors, cache sizes and cache block sizes. From these measurements, we found out the shared data in TPC-B largely bear quite different sharing characteristics from those in scientific applications.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.911-917
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• 2023

In today's world, we find ourselves facing energy crises due to factors such as war and climate crises. To prepare for these energy crises, many researchers continue to study systems related to energy monitoring and conservation, such as energy management systems, energy monitoring, and energy conservation. In line with these efforts, nations are making it mandatory for energy-consuming facilities to implement these systems. However, these facilities, limited by space and energy constraints, are exploring ways to improve. This research explores the operation of a data collection system using low-performance embedded devices. In this context, it proves that an optimized version of RocksDB, a Key-Value store, outperforms traditional databases when it comes to time-series data. Furthermore, a comprehensive database evaluation tool was employed to assess various databases, including optimized RocksDB and regular RocksDB. In addition, heterogeneous databases and evaluations are conducted using a UD Benchmark tool to evaluate them. As a result, we were able to see that on devices with low performance, the time required was up to 11 times shorter than that of other databases.

• Journal of KIISE:Databases
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• v.36 no.5
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• pp.374-385
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• 2009

Flash memory becomes increasingly popular as data storage for various devices because of its versatile features such as non-volatility, light weight, low power consumption, and shock resistance. Flash memory, however, has some distinct characteristics that make today's disk-based database technology unsuitable, such as no in-place update and the asymmetric speed of read and write operations. As a result, most traditional disk-based database systems may not provide the best attainable performance on flash memory. To maximize the database performance on flash memory, some approaches have been proposed where only the changes made to the database, i.e., logs, are written to another empty place that has born erased in advance. In this paper, we propose an efficient log management scheme for flash-based database systems. Unlike the previous approaches, the proposed approach stores logs in specially allocated blocks, called log blocks. By evenly distributing logs across log blocks, the proposed approach can significantly reduce the number of write and erase operations. Our performance evaluation shows that the proposed approaches can improve the overall system performance by reducing the number of write and erase operation compared to the previous ones.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.11-19
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• 2014

In this paper, we design an intelligent agent system with the data mining module and information fusion module as the core components of the system and investigate the possibility for the medical expert system. In the data mining module, fuzzy neural network, OFUN-NET analyzes multi-view data and produces fuzzy cluster knowledge base. In the information fusion module and application module, they serve the diagnosis result with possibility degree and useful information for diagnosis, such as uncertainty decision status or detection of asymmetry. We also present the experiment results on the BI-RADS-based feature data set selected form DDSM benchmark database. They show higher classification accuracy than conventional methods and the feasibility of the system as a computer aided diagnosis system.