• Title/Summary/Keyword: MR-트리

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Making Cache-Conscious CCMR-trees for Main Memory Indexing (주기억 데이타베이스 인덱싱을 위한 CCMR-트리)

  • 윤석우;김경창
    • 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.

Delay Operation Techniques for Efficient MR-Tree on Nand Flash Memory (낸드 플래시 메모리 상에서 효율적인 MR-트리 동작을 위한 지연 연산 기법)

  • Lee, Hyun-Seung;Song, Ha-Yoon;Kim, Kyung-Chang
    • 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.

Design and Implementation of a Main-Memory Database System for Real-time Mobile GIS Application (실시간 모바일 GIS 응용 구축을 위한 주기억장치 데이터베이스 시스템 설계 및 구현)

  • Kang, Eun-Ho;Yun, Suk-Woo;Kim, Kyung-Chang
    • The KIPS Transactions:PartD
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    • v.11D no.1
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    • pp.11-22
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    • 2004
  • As random access memory chip gets cheaper, it becomes affordable to realize main memory-based database systems. Consequently, reducing cache misses emerges as the most important issue in current main memory databases, in which CPU speeds have been increasing at 60% per year, compared to the memory speeds at 10% per you. In this paper, we design and implement a main-memory database system for real-time mobile GIS. Our system is composed of 5 modules: the interface manager provides the interface for PDA users; the memory data manager controls spatial and non-spatial data in main-memory using virtual memory techniques; the query manager processes spatial and non-spatial query : the index manager manages the MR-tree index for spatial data and the T-tree index for non-spatial index : the GIS server interface provides the interface with disk-based GIS. The MR-tree proposed propagates node splits upward only if one of the internal nodes on the insertion path has empty space. Thus, the internal nodes of the MR-tree are almost 100% full. Our experimental study shows that the two-dimensional MR-tree performs search up to 2.4 times faster than the ordinary R-tree. To use virtual memory techniques, the memory data manager uses page tables for spatial data, non- spatial data, T-tree and MR-tree. And, it uses indirect addressing techniques for fast reloading from disk.

MR-Tree: A Mapping-based R-Tree for Efficient Spatial Searching (Mr-Tree: 효율적인 공간 검색을 위한 매핑 기반 R-Tree)

  • Kang, Hong-Koo;Shin, In-Su;Kim, Joung-Joon;Han, Ki-Joon
    • Spatial Information Research
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    • v.18 no.4
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    • pp.109-120
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    • 2010
  • Recently, due to rapid increasement of spatial data collected from various geosensors in u-GIS environments, the importance of spatial index for efficient search of large spatial data is rising gradually. Especially, researches based R-Tree to improve search performance of spatial data have been actively performed. These previous researches focus on reducing overlaps between nodes or the height of the R -Tree. However, these can not solve an unnecessary node access problem efficiently occurred in tree traversal. In this paper, we propose a MR-Tree(Mapping-based R-Tree) to solve this problem and to support efficient search of large spatial data. The MR-Tree can improve search performance by using a mapping tree for direct access to leaf nodes of the R-Tree without tree traversal. The mapping tree is composed with MBRs and pointers of R-Tree leaf nodes associating each partition which is made by splitting data area repeatedly along dimensions. Especially, the MR-Tree can be adopted in various variations of the R-Tree easily without a modification of the R-Tree structure. In addition, because the mapping tree is constructed in main memory, search time can be greatly reduced. Finally, we proved superiority of MR-Tree performance through experiments.

SQMR-tree: An Efficient Hybrid Index Structure for Large Spatial Data (SQMR-tree: 대용량 공간 데이타를 위한 효율적인 하이브리드 인덱스 구조)

  • Shin, In-Su;Kim, Joung-Joon;Kang, Hong-Koo;Han, Ki-Joon
    • Spatial Information Research
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    • v.19 no.4
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    • pp.45-54
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    • 2011
  • In this paper, we propose a hybrid index structure, called the SQMR-tree(Spatial Quad MR-tree) that can process spatial data efficiently by combining advantages of the MR-tree and the SQR-tree. The MR-tree is an extended R-tree using a mapping tree to access directly to leaf nodes of the R-tree and the SQR-tree is a combination of the SQ-tree(Spatial Quad-tree) which is an extended Quad-tree to process spatial objects with non-zero area and the R-tree which actually stores spatial objects and are associated with each leaf node of the SQ-tree. The SQMR-tree consists of the SQR-tree as the base structure and the mapping trees associated with each R-tree of the SQR-tree. Therefore, because spatial objects are distributedly inserted into several R-trees and only R-trees intersected with the query area are accessed to process spatial queries like the SQR-tree, the query processing cost of the SQMR-tree can be reduced. Moreover, the search performance of the SQMR-tree is improved by using the mapping trees to access directly to leaf nodes of the R-tree without tree traversal like the MR-tree. Finally, we proved superiority of the SQMR-tree through experiments.

Voice Personality Transformation Using a Multiple Response Classification and Regression Tree (다중 응답 분류회귀트리를 이용한 음성 개성 변환)

  • 이기승
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.3
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    • pp.253-261
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    • 2004
  • In this paper, a new voice personality transformation method is proposed. which modifies speaker-dependent feature variables in the speech signals. The proposed method takes the cepstrum vectors and pitch as the transformation paremeters, which represent vocal tract transfer function and excitation signals, respectively. To transform these parameters, a multiple response classification and regression tree (MR-CART) is employed. MR-CART is the vector extended version of a conventional CART, whose response is given by the vector form. We evaluated the performance of the proposed method by comparing with a previously proposed codebook mapping method. We also quantitatively analyzed the performance of voice transformation and the complexities according to various observations. From the experimental results for 4 speakers, the proposed method objectively outperforms a conventional codebook mapping method. and we also observed that the transformed speech sounds closer to target speech.

Tree based Route Optimization in Nested NEMO Environment (중첩 NEMO 환경에서 트리 기반 라우트 최적화 기법)

  • Lim, Hyung-Jin;Chung, Tai-Myoung
    • Journal of Internet Computing and Services
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    • v.9 no.1
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    • pp.9-19
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    • 2008
  • This paper propose the issue of connecting nested NEMO (Network Nobility) networks to global IPv6 networks, while supporting IPv6 mobility. Specifically, we consider a self-addressing including topology information IPv6-enabled NEMO infrastructure. The proposed self-organization addressing protocol automatically organized mobile routers into free architecture and configuration their global IPv6 addresses. BU(binding update) to MR own HA and internal rouging, hosed on longest prefix matching and soft state routing cache, are specially designed for IPv6-based NEMO. In conclusion, numeric analysis ore conducted to show more efficiency of the proposed routing protocols than other RO (Route Optimization) approaches.

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Classification of Brain MR Images using 2 Level Decision Tree Learning (2 단계 결정 트리 학습을 이용한 뇌 MR 영상 분류)

  • Kim, Yong-Uk;Kim, Jun-Tae
    • Proceedings of the Korea Information Processing Society Conference
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    • 2001.04a
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    • pp.341-344
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    • 2001
  • 본 논문에서는 학습을 수행하여 뇌 MR 이미지를 자동으로 분류하고 검색하는 시스템을 설계하였다. 이미지로부터 얻을 수 있는 정보는 크게 두 가지 부류로 나눌 수 있다. 이미지 자체로부터 얻을수 있는 크기, 색상, 질감, 윤곽선 등의 하위레벨(low-level) 정보가 있고, 이미지 의미 해석에서 오는 전이, 포함, 방향, 등의 상위레벨(high-level) 정보가 있다. 이 논문은 의료 이미지에 대하여 상위 및 하위 레벨 정보의 각 특징을 살리고 효과적으로 검색하기 위해, 두 부류의 이미지 정보에 대한 결정 트리(Decision Tree) 학습을 2 단계로 적용하여 이미지를 분류하도록 시스템을 설계하였다.

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Efficient Compression of MR Images Using Fractal Coding in Wavelet Transform Domain (웨이브릿 변환 영역에서의 프랙탈 부호화를 이용한 효율적 MR 영상 압축)

  • Bae S.H.;Yoon O.K.;Kim J.H.;Park C.H.;Lee S.K.;Park K.H.;Kim H.S.
    • Journal of Biomedical Engineering Research
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    • v.21 no.3 s.61
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    • pp.247-254
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    • 2000
  • We propose an efficient MR image compression technique using fractal coding in wavelet transform domain. In the Proposed method , we construct significant coefficient trees with the absolute values of discrete wavelet transform coefficients and then perform the fractal coding with the information of significant coefficients having high energy. For MR images, most Pixels including background have very low gray level values, the number of significant coefficients is small. so we can expect high compression rate. In addition. since this method uses the fractal coding in wavelet transform domain, blocking artifact is reduced prominently and edges sensitive to human visual system are well preserved. As a result of computer simulation, we obtained the reconstructed images with better quality than those by JPEG at the low bit rates below 0.33[bpp].

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