• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.732-736
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• 2010

Processing a large amount of data becomes more important than ever. Particularly, the information queries which require multi-dimensional record scan can be efficiently implemented with SIMD instruction sets. In this article, we present a SIMD record scan technique which employs row-based scanning. Our technique is different from existing SIMD techniques for predicate processes and aggregate operations. Those techniques apply SIMD instructions to the attributes in the same column of the database, exploiting the column-based record organization of the in-memory database systems. Whereas, our SIMD technique is useful for multi-dimensional record scanning. As the sizes of registers and the memory become larger, our row-based SIMD scan can have bigger impact on the performance. Moreover, since our technique is orthogonal to the parallelization techniques for multi-core processors, it can be applied to both uni-processors and multi-core processors without too many changes in the software architectures.

• Journal of Korea Spatial Information System Society
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• v.6 no.1 s.11
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• pp.3-17
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• 2004

With the rapid growth of the Internet geographic information services through the WWW such as a location-based service and so on. Web GISs (Geographic Information Systems) have also come to be a cluster-based architecture like most other information systems. That is, in order to guarntee high quality of geographic information service without regard to the rapid growth of the number of users, web GISs need cluster-based architecture that will be cost-effective and have high availability and scalability. This paper proposes the design of the cluster-based web GIS with high availability and scalability. For this, each node within a cluster-based web GIS consists of main memory spatial databases which accomplish role of caching by using data declustering and the locality of spatial query. Not only simple region queries but also the proposed system processed spatial join queries effectively. Compare to the existing method. Parallel R-tree spatial join for a shared-Nothing architecture, the result of simulation experiments represents that the proposed spatial join method achieves improvement of performance respectively 23% and 30% as data quantity and nodes of cluster become large.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.53-73
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• 2006

Recently, the need for Location-Based Services (LBS) has increased due to the development of mobile devices, such as PDAs, cellular phones and GPS. As a moving object database that stores and manages the positions of moving objects is the core technology of LBS, the scheme for maintaining the main memory DBMS to the server is necessary to store and process frequent reported positions of moving objects efficiently. However, previous works on a moving object database have studied mostly a disk based moving object index that is not guaranteed to work efficiently in the main memory DBMS because these indexes did not consider characteristics of the main memory. It is necessary to study the main memory index scheme for a moving object database. In this paper, we propose the main memory index scheme based on the R-tree for storing and processing positions of moving objects efficiently in the main memory DBMS. The proposed index scheme, which uses a growing node structure, prevents the splitting cost from increasing by delaying the node splitting when a node overflows. The proposed scheme also improves the search performance by using a MergeAndSplit policy for reducing overlaps between nodes and a LargeDomainNodeSplit policy for reducing a ratio of a domain size occupied by node's MBRs. Our experiments show that the proposed index scheme outperforms the existing index scheme on the maximum 30% for range queries.

• The KIPS Transactions:PartD
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• v.12D no.5 s.101
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• pp.689-698
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• 2005

Various systems are used to provide the location based services. But, the existing systems have some problems which have difficulties in dealing with faster services for above million people. In order to solve it, a multi-level DBMS which supports both fast data processing and large data management support should be used. The multi-level DBMS with snapshots has all the data existing in disk database and the data which are required to be processed for fast processing are managed in main memory database as snapshots. To optimize performance of this system for location based services, the query classification component which classifies the queries for efficient snapshot usage is needed. In this paper, the query classification component in multi-level DBMS for location based services is designed and implemented. The proposed component classifies queries into three types: (1) memory query, (2) disk query, (3) hybrid query, and increases the rate of snapshot usage. In addition, it applies division mechanisms which divide aspatial and spatial filter condition for partial snapshot usage. Hence, the proposed component enhances system performance by maximizing the usage of snapshot as a result of the efficient query classification.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11c
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• pp.1383-1386
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• 2003

최근 공간 데이터베이스의 선택률 추정 문제에 대한 관심이 증가하면서, 데이터분포의 편중, 중복 계산, 메모리 공간 최소화등의 문제를 고려한 다양한 기법들이 제안되고 있다. 그러나 이들 기법들 간의 성능 분석을 통한 비교평가는 이루어지지 않고 있다. 따라서, 이 논문에서는 공간 영역 객체의 범위질의에 관한 선택률 추정 기법인 Min-Skew, 웨이블릿, 누적밀도, 오일러 히스토그램을 비교 분석한다. 즉, 실제 데이터셋을 기반으로 여러 형태의 질의에 대한 성능 비교를 통해 각 기법들을 비교 평가한다. 이 연구 결과는 새로운 기법 도출에 이용될 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.10
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• pp.2597-2604
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• 1996

본 논문에서는 주기억 데이터베이스 시스템에서의 효율적인 데이터 처리를 위하여 T*-트리라는 새로운 색인구조를 제시한다. T*-트리 색인구조는 기존의 디스크를 기반으로 하는 색인기법과 달리 모든 데이터가 주기억장치에 적재되어 있는 시스템에서 보다 빠른 데이터 접근과 메모리 공간의 효율적인 사용을 위해 주기억 데이터베이스 시스템에서 주로 사용되고 있는 T*-트리색인구조의 장점은 그대로 계승하면서 단점을 보완한 인덱스 구조이다. 본 논문에서 제시하는 T*-트리는 데이터 아이템에 대한 검색과 저장공간의 활용면에서는 T*-트리와 대동소이한 성능을 가지고 있으나, 범위 질의에서와 데이터 아이템에 대한 검색과 삭제시 중간노드에서의 노드간의 순회경로를 줄임으로써 보다 향상된 성능을 보여준다. 또한 T*-트리와 스레드 이진트리를 조합하는 경우에는 순회경로가 다소 단축되지만 중간노드에서 자신보다 높은 레벨의 후속 노드로의 순회는 기존의 인오더 트리 순회에 의존하지만, T*-트리에서는 후위포인터를 이용하므로 직접순회가 가능하게 된다. 본 논문에서는 제안된 T*-트리의 구조와 T*-트리의 검색, 삽입 및 삭제 연산을 위한 알고리즘을 설명한 후, 기존의 T*-트리와 성능분석을 실시하고 그 결과를 제시한다. 성능 분석결과 T*-트리는 데이터 검색의 경우 기존의 T*-트리와 거의 동일한 성능을 보였으며, 삽입과 식제등 색인구조의 변경시는 약간의 성능향상을 보였으나, 범위질의와 순차질의에서는 매우 향상된 성능을 나타냈다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.28-33
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• 2003

This paper proposes a database index and retrieval method using the PCA(Principal Component Analysis). We perform a scene change detection and key frame extraction from the DC Image constructed by DCT DC coefficients in the compressed video stream that is video compression standard such as MPEG. In the extracted key frame, we use the PCA, then we can make codebook that has a statistical data as a codeword, which is saved as a database index. We also provide retrieval image that are similar to user's query image in a video database. As a result of experiments, we confirmed that the proposed method clearly showed superior performance in video retrieval and reduced computation time and memory space.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.841-850
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• 1999

Many commercial database systems maintain histograms to summarize the contents of relations, permit efficient estimation of query result sizes, and access plan costs. In spatial database systems, most query predicates consist of topological relationship between spatial objects, and ti is ver important to estimate the selectivity of those predicates for spatial query optimizer. In this paper, we propose a selectivity estimation scheme for spatial topological predicates based on the multi-dimensional histogram and the transformation scheme. Proposed scheme applies two partition strategies on transformed object space to generate spatial histogram, and estimates the selectivity of topological predicates based on the topological characteristic of transformed space. Proposed scheme provides a way for estimating the selectivity without too much memory space usage and additional I/Os in spatial query optimizer.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.167-176
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• 2012

In this paper we design and implement a new Hybrid Equipment Data Acquisition System (HEDAS) for data collection of semiconductor and optoelectronic manufacturing equipments in the equipment engineering system(EES) framework. The amount of the data collected from equipments have increased rapidly in equipment engineering system. The proposed HEDAS efficiently handles a large amount of real-time equipment data generated from EES framework. It also can support the real-time ESS applications as well as non real-time ESS applications. For the real-time EES applications, it performs high-speed real-time processing that uses continuous query and filtering techniques based on memory buffers. The HEDAS can optionally store non real-time equipment data using a HEDAS-based database or a traditional DBMS-based database. In particular, The proposed HEDAS offers the compression indexing based on the timestamp of data and query processing technique saving the cost of disks storage against extremely increasing equipment data. The HEDAS is efficient system to collect huge real-time and non real-time equipment data and transmit the collected equipment data to several EES applications in EES framework.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.3
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• pp.509-516
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• 2008

Recently, the operator modules to control external devices are concerned about automatic management system to process continuously changed signals. These signals are the stream data of which characteristics are several numbers. a short report interval and asynchronous report time. It is necessary that the system brings about high accuracy and real time process for stream data. The typical queries of these systems consist of the current query to search the latest signal value, the snapshot query at a past time, the sliding window query from a past time to current. In this paper, we propose the efficient method to manage the above signals by using a file structured database in small-size operating systems. We also propose a query model to accommodate various queries including the sliding window query. The file database in the QNX adopts a delta version and a shared memory buffering method for the resource limit of a small storage and a low computing power.