• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.40-46
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• 2003

The high-performance processors have recently employed sophisticated techniques to overlap and simultaneously execute multiple computation and memory operations. For the query processing of database management systems, those hardware characteristics are the important research issue. The latest works show that the cache miss penalty between main memory and CPU becomes new bottlenecks and the branch misprediction causes serious resource-waste. An effcient algorithm for query processing of aggregate functions considering these hardware characteristics was proposed in this dissertation.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.1023-1043
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• 2010

As main memory get cheaper, it becomes increasingly affordable to load entire index of DBMS and to access the index. Since speed gap between CPU and main memory is growing bigger, many researches to reduce a cost of main memory access are under the progress. As one of those, cache conscious trees can reduce the cost of main memory access. Since cache conscious trees reduce the number of cache miss by compressing data in node, cache conscious trees can reduce the cost of main memory. Existing cache conscious trees use only fixed one compression technique without consideration of properties of data in node. First, this paper proposes the DC-tree that uses various compression techniques and change data layout in a node according to properties of data in order to reduce cache miss. Second, this paper proposes the level of compression locality that describes properties of data in node by formula. Third, this paper proposes Forced Partial Decomposition (FPD) that reduces the nutter of cache miss. DC-trees outperform 1.7X than B+-tree, 1.5X than simple prefix B+-tree, and 1.3X than pkB-tree, in terms of the number of cache misses. Since proposed DC-trees can be adopted in commercial main memory database system, we believe that DC-trees are practical result.

• Journal of KIISE:Databases
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• v.30 no.6
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• pp.651-665
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• 2003

To reduce cache misses emerges as the most important issue in today's situation of main memory databases, in which CPU speeds have been increasing at 60% per year, and memory speeds at 10% per year. Recent researches have demonstrated that cache-conscious index structure such as the CR-tree outperforms the R-tree variants. Its search performance can be poor than the original R-tree, however, since it uses a lossy compression scheme. In this paper, we propose alternatively a cache-conscious version of the R-tree, which we call MR-tree. The MR-tree propagates node splits upward only if one of the internal nodes on the insertion path has empty room. Thus, the internal nodes of the MR-tree are almost 100% full. In case there is no empty room on the insertion path, a newly-created leaf simply becomes a child of the split leaf. The height of the MR-tree increases according to the sequence of inserting objects. Thus, the HeightBalance algorithm is executed when unbalanced heights of child nodes are detected. Additionally, we also propose the CCMR-tree in order to build a more cache-conscious MR-tree. Our experimental and analytical study shows that the two-dimensional MR-tree performs search up to 2.4times faster than the ordinary R-tree while maintaining slightly better update performance and using similar memory space.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.191-194
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• 2001

The availability of the inexpensive, large main memories coupled with the demand for faster response time are bringing a new perspective to database technology. The Web GIS used by u unspecified number of general public in the internet needs high speed response time and frequent data retrieval for spatial analysis rather than data update. Therefore, it is appropriate to use main memory as a underlying storage structures for the Web GIS data. In this paper, we propose a data representation method based on relative coordinates and the size of the MBR. The method is able to compress the spatial data widely used in the Web GIS into smaller volume of memory. We also propose a memory resident spatial index with simple mechanism for processing point and region queries. The performance test shows that the index is suitable for managing the skewed data in terms of the size of the index and the number of the MBR intersection check operations.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.406-409
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• 2008

Clustering data streams has an importance over many applications like sensor networks. Existing hierarchical methods follow a semi fuzzy clustering that yields duplicate clusters. In order to solve the problems, we propose an extended online divisive agglomerative clustering on data streams. It builds a tree-like top-down hierarchy of clusters that evolves with data streams using geometric time frame for snapshots. It is an enhancement of the Online Divisive Agglomerative Clustering (ODAC) with a pruning strategy to avoid duplicate clusters. Our main features are providing update time and memory space which is independent of the number of examples on data streams. It can be utilized for clustering sensor data and network monitoring as well as web click streams.

• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.183-193
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• 2003

The importance of XML data and their database supports in a mobile terminal system is on the increase. It leads to active research for embedded XML database systems. In order to handle in documents, DOM API should be supported. The existing DOM API is not suitable for the embedded system with limited resource because the DOM tree requires a large space on main memory. Considering poor resource of embedded systems, we present persistent DOM which is implemented on Berkeley DB and DOMdbm which manages it.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.51-58
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• 2007

The shared-nothing multiprocessor architecture has advantages in scalability, this architecture has been adopted in many multiprocessor database system. But, if the data are not uniformly distributed across the processors, load will be unbalanced. Therefore, the whole system performance will deteriorate. This is the data skew problem, which usually occurs in processing parallel hash join. Balancing the load before performing join will resolve this problem efficiently and the whole system performance can be improved. In this paper, we will present an algorithm using merit of very large memory to reduce disk access overhead in performing load balancing and to efficiently solve the data skew problem. Also, we will present analytical model of our new algorithm and present the result of some performance study we made comparing our algorithm with the other algorithms in handling data skew.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.157-159
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• 2004

정보통신 기술의 발달로 자치단체에서 개별적으로 운영되던 업무별 단위시스템을 단일화 또는 연계하여 자료를 공동 활용하려는 노력이 계속되고 있다 하지만 타 시스템의 자료를 실시간으로 검색함에 있어 빠른 응답시간이 요구되며, 검색건수 증가에 따른 수행지연으로 인한 문제가 되고 있다. 따라서 본 논문에서는 검색 대상 자료를 본 시스템의 메모리에 상주시켜 연계자료에 대한 검색속도를 높이고 수행지연에 의한 병목현상을 해결할 수 있는 방안을 제시하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.118-120
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• 2002

본 논문에서는 주기억 데이터베이스 시스템의 메모리 벤치마크를 설계하고 실제 사용되는 주기억 데이터베이스 시스템에 설계된 벤치마크를 구현하였다. 벤치마크를 통해서 주기억 데이터베이스 시스템에서 이용된 메모리 최적화 기법을 통해 줄어든 메모리 양의 평가와 주기억 데이터베이스에 저장된 데이터에 비례해서 업무 작업 시에 필요로 하는 메모리 소요량을 예측할 수 있고, 여러 데이터베이스간의 상대적인 비교를 할 수 있도록 한다

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.794-796
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• 2003

주기억 데이타베이스 시스템은 기존의 디스크 기반 데이타베이스 시스템과 달리 빠른 처리속도와 주기억 장치의 효율적인 사용이 주된 관심 사항이다. 본 논문에서는 주기억 데이타베이스에서 공간 데이터를 위한 효율적인 인덱스구조를 제시한다. 기존에 제시된 주기억 데이타베이스를 위한 인덱스 기법으로는 T-트리, Hash 계열 기법등이 제시되었으나, 이러한 모든 인덱스 기법은 1차원 데이타를 위한 인덱스 기법으로 공간 데이타에는 적용이 불가능하다. 이러한 제약을 극복하기 위해서 본 논문에서는 T-트리에 R-트리 개념을 추가 하였다.