• Title/Summary/Keyword: Index기법

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An Efficient Phantom Protection Method for Concurrency Control in Multi-dimensional Index Structures (다차원 색인구조에서 동시성제어를 위한 효율적인 유령 방지 기법)

  • Yun Jong-Hyun;Song Seok-Il;Yoo Jae-Soo;Lee Seok-Jae
    • The Journal of the Korea Contents Association
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    • v.5 no.1
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    • pp.157-167
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    • 2005
  • In this paper, we propose a new phantom protection method for multi-dimensional index structures. The proposed method uses a hybrid approach of predicate locking and granular locking mechanisms. The proposed mechanism is independent of the types of multi-dimensional index structures, i.e., it can be applied to all types of index structures such as tree-based, file-based and hash-based index structures. Also, it achieves low development cost and high concurrency with low lock overhead. It is shown through various experiments that the proposed method outperforms existing phantom protection methods for multi-dimensional index structures.

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Efficient Index Reconstruction Methods using a Partial Index in a Spatial Data Warehouse (공간 데이터 웨어하우스에서 부분 색인을 이용한 효율적인 색인 재구축 기법)

  • Kwak, Dong-Uk;Jeong, Young-Cheol;You, Byeong-Seob;Kim, Jae-Hong;Bae, Hae-Young
    • Journal of Korea Spatial Information System Society
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    • v.7 no.3 s.15
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    • pp.119-130
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    • 2005
  • A spatial data warehouse is a system that stores geographical information as a subject oriented, integrated, time-variant, non-volatile collection for efficiently supporting decision. This system consists of a builder and a spatial data warehouse server. A spatial data warehouse server suspends user services, stores transferred data in the data repository and constructs index using stored data for short response time. Existing methods that construct index are bulk-insertion and index transfer methods. The Bulk-insertion method has high clustering cost for constructing index and searching cost. The Index transfer method has improper for the index reconstruction method of a spatial data warehouse where periodic source data are inserted. In this paper, the efficient index reconstruction method using a partial index in a spatial data warehouse is proposed. This method is an efficient reconstruction method that transfers a partial index and stores a partial index with expecting physical location. This method clusters a spatial data making it suitable to construct index and change treated clusters to a partial index and transfers pages that store a partial index. A spatial data warehouse server reserves sequent physical space of a disk and stores a partial index in the reserved space. Through inserting a partial index into constructed index in a spatial data warehouse server, searching, splitting, remodifing costs are reduced to the minimum.

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View Index Technique using Signatures in Relational Databases (관계 데이타베이스에서 시그니쳐를 이용한 뷰인덱스 기법)

  • Yong, Hwan-Seung
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.4
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    • pp.757-765
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    • 1996
  • View index techniques are proposed to process queries on views. Signature referencing techniques keep pointers with signatures of the referred object when there is any reference relationship between objects. When queries having conditions on referred object are give, disk I/Os can be reduced by checking conditions using stored signatures. Signature view index techniques proposed in this paper apply signature referencing techniques to view index by keeping not only tuple identifiers but also signatures for the tuple. When queries having conditions on views regiven, we can retrieve only tuples from a view index which satisfy given conditions by checking those with stored signatures.

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Lazy Bulk Insertion Method of Moving Objects Using Index Structure Estimation (색인 구조 예측을 통한 이동체의 지연 다량 삽입 기법)

  • Kim, Jeong-Hyun;Park, Sun-Young;Jang, Hyong-Il;Kim, Ho-Suk;Bae, Hae-Young
    • Journal of Korea Spatial Information System Society
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    • v.7 no.3 s.15
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    • pp.55-65
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    • 2005
  • This paper presents a bulk insertion technique for efficiently inserting data items. Traditional moving object database focused on efficient query processing that happens mainly after index building. Traditional index structures rarely considered disk I/O overhead for index rebuilding by inserting data items. This paper, to solve this problem, describes a new bulk insertion technique which efficiently induces the current positions of moving objects and reduces update cost greatly. This technique uses buffering technique for bulk insertion in spatial index structures such as R-tree. To analyze split or merge node, we add a secondary index for information management on leaf node of primary index. And operations are classified to reduce unnecessary insertion and deletion. This technique decides processing order of moving objects, which minimize split and merge cost as a result of update operations. Experimental results show that this technique reduces insertion cost as compared with existing insertion techniques.

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An Indexing Technique for Object-Oriented Geographical Databases (객체지향 지리정보 데이터베이스를 위한 색인기법)

  • Bu, Ki-Dong
    • Journal of the Korean association of regional geographers
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    • v.3 no.2
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    • pp.105-120
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    • 1997
  • One of the most important issues of object-oriented geographical database system is to develop an indexing technique which enables more efficient I/O processing within aggregation hierarchy or inheritance hierarchy. Up to present, several indexing schemes have been developed for this purpose. However, they have separately focused on aggregation hierarchy or inheritance hierarchy of object-oriented data model. A recent research is proposing a nested-inherited index which combines these two hierarchies simultaneously. However, this new index has some weak points. It has high storage costs related to its use of auxiliary index. Also, it cannot clearly represent the inheritance relationship among classes within its index structure. To solve these problems, this thesis proposes a pointer-chain index. Using pointer chain directory, this index composes a hierarchy-typed chain to show the hierarchical relationship among classes within inheritance hierarchy. By doing these, it could fetch the OID list of objects to be retrieved more easily than before. In addition, the pointer chain directory structure could accurately recognize target cases and subclasses and deal with "select-all" typed query without collection of schema semantic information. Also, it could avoid the redundant data storing, which usually happens in the process of using auxiliary index. This study evaluates the performance of pointer chain indexing technique by way of simulation method to compare nested-inherited index. According to this simulation, the pointer chain index is proved to be more efficient with regard to storage cost than nested-inherited index. Especially in terms of retrieval operation, it shows efficient performance to that of nested-inherited index.

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Complexity Reduction Algorithm for Quantized EGT Codebook Searching in Multiple Antenna Systems (다중 안테나 시스템에서 양자화된 동 이득 전송 기법의 코드북 검색 복잡도 감쇄 기법)

  • Park, Noe-Yoon;Kim, Young-Ju
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.22 no.1
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    • pp.98-105
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    • 2011
  • Reduced complexity codebook searching for Quantized Equal Gain Transmission(QEGT) is proposed over MIMO-OFDM systems. QEGT codebook is divided into M groups of Q index members. Each group has a representative index. At the 1st stage only the representative indices are searched then the best index is selected. At the 2nd stage the optimum index is determined only among the group of the selected representative index. This strategy reduces the overall index search algorithm comparing to the conventional methods. Monte-Carlo simulation shows that the searching complexity is reduced, but the link-level performance is still almost the same as the conventional methods when the number of transmission antennas are 3 to 7.

Search scheme for parallel spatial index (병렬 공간 색인을 위한 검색 기법)

  • Seo, Young-Duk
    • Journal of Korea Spatial Information System Society
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    • v.7 no.2 s.14
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    • pp.81-89
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    • 2005
  • Declustering and parallel index structures are important research areas to improve a performance of databases. Previous researches proposed several distribution schemes for parallel R-trees, however there is no search schemes to be suitable for the index. In this paper, we propose schemes to improve the performance of range queries for distribute parallel indexes. The proposed schemes use the features that a parallel disk can read multiple nodes from various disks. The proposed schemes are verified using various implementations and performance evaluations. We propose new schemes which can read multiple nodes from multiple disks in contrast that to the previous schemes which can read a node from disk. The experimental evaluation shows that the proposed schemes give us the performance improvement by 40% from the previous researches.

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KDBcs-Tree : An Efficient Cache Conscious KDB-Tree for Multidimentional Data (KDBcs-트리 : 캐시를 고려한 효율적인 KDB-트리)

  • Yeo, Myung-Ho;Min, Young-Soo;Yoo, Jae-Soo
    • Journal of KIISE:Databases
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    • v.34 no.4
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    • pp.328-342
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    • 2007
  • We propose a new cache conscious indexing structure for processing frequently updated data efficiently. Our proposed index structure is based on a KDB-Tree, one of the representative index structures based on space partitioning techniques. In this paper, we propose a data compression technique and a pointer elimination technique to increase the utilization of a cache line. To show our proposed index structure's superiority, we compare our index structure with variants of the CR-tree(e.g. the FF CR-tree and the SE CR-tree) in a variety of environments. As a result, our experimental results show that the proposed index structure achieves about 85%, 97%, and 86% performance improvements over the existing index structures in terms of insertion, update and cache-utilization, respectively.

PPMMLG : A Phantom Protection Method based on Multi-Level Grid Technique for Multi-dimensional Index Structures (PPMMLG :다차원 색인구조를 위한 다중 레벨 그리드 방식의 유령현상 방지 기법)

  • Lee, Seok-Jae;Song, Seok-Il;Yoo, Jae-Soo
    • Journal of KIISE:Databases
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    • v.32 no.3
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    • pp.304-314
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    • 2005
  • In this paper, we propose a new phantom protection method for multi-dimensional index structures that uses multi-level grid technique. The proposed mechanism is independent of the types of multi-dimensional index structures, i.e., it can be applied to all types of index structures such as tree-based, file-based and hash-based index structures. Also, it achieves low development cost and high concurrency with low lock overhead. It is shown through various experiments that the proposed method outperforms existing phantom protection methods for multi-dimensional index structures.

Two-Dimensional Grouping Index for Efficient Processing of XML Filtering Queries (XML 필터링 질의의 효율적 처리를 위한 이차원 그룹핑 색인기법)

  • Yeo, Dae-Hwi;Lee, Jong-Hak
    • Journal of Information Technology and Architecture
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    • v.10 no.1
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    • pp.123-135
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    • 2013
  • This paper presents a two-dimensional grouping index(2DG-index) for efficient processing of XML filtering queries. Recently, many index techniques have been suggested for the efficient processing of structural relationships among the elements in the XML database such as an ancestor- descendant and a parent-child relationship. However, these index techniques focus on simple path queries, and don't consider the path queries that include a condition value for filtering. The 2DG-index is an index structure that deals with the problem of clustering index entries in the twodimensional domain space that consists of a XML path identifier domain and a filtering data value domain. For performance evaluation, we have compared our proposed 2DG-index with the conventional one dimensional index structure such as the data grouping index (DG-index) and the path grouping index (PG-index). As the result of the performance evaluations, we have verified that our proposed 2DG-index can efficiently support the query processing in XML databases according to the query types.