• Title/Summary/Keyword: R-Tree

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mkNN Query Processing Method based on $R^m$-tree for Spatial Objects with m-types (m-유형 공간객체를 위한 $R^m$-tree기반의 mk-최근접질의 처리기법)

  • Jang, Dong-Jue;An, Soo-Yeon;Jung, Sung-Won
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06c
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    • pp.45-48
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    • 2011
  • 본 논문에서는 다양한 타입의 위치기반 데이터들을 하나의 R-tree로 통합합 $R^m$-tree의 구조와 이 $R^m$-tree를 이용하여 질의 포인트로부터 각 타입에서 k개의 가까운 위치기반 데이터를 찾는 mkNN(multi-type k nearest neighbor) 질의 처리기법을 제안하였다. 특히, 다양한 타입의 위치기반 데이터들을 각 타입별로 독립된 R-tree로 유지하지 않고, 하나의 $R^m$-tree로 통합하여 관리함으로써 mkNN 질의 처리시 같은 레벨의 공간의 반복탐색을 줄일 수 있도록 고안하였다. 그리고 각 타입 t에 대한 위치데이터를 관리하는 부가적인 타입정보 자료구조로서 위치정보를 담은 TMBR, 데이터 개수정보를 담은 $I_t$-entry를 새로이 고안하여 mkNN질의 처리시 효율적인 휠터링(filtering)과 검색과정이 이루어지도록 하였다.

PR-Tree: An Extended R-Tree Indexing Method using Prefetching in Main Memory (PR-Tree: 메인 메모리에서 선반입을 적용한 확장된 R-tree 색인 기법)

  • Kang, Hong-Koo;Kim, Dong-O;Hong, Dong-Sook;Han, Ki-Joon
    • 한국공간정보시스템학회:학술대회논문집
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    • 2003.11a
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    • pp.123-128
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    • 2003
  • 최근 프로세서와 메인 메모리간의 속도 차이가 커지면서 캐시 실패가 메인 메모리에서 동작하는 R-Tree의 성능 저하에 미치는 영향이 커짐에 따라 캐시 실패를 줄여 캐시 성능을 개선하려는 연구가 많이 진행되고 있다. 일반적인 캐시 성능 개선 방법은 엔트리 정보를 줄설 노드에 더 않은 엔트리를 저장함으로써 펜-아웃(fanout)을 증가시키고 캐시 실패를 최소화한다. 그러나 이러한 방법은 엔트리 정보를 줄이는 추가 연산으로 인해 갱신 성능이 떨어지고, 노드간 이동시 발생하는 캐시 실패는 여전히 해결하지 못하고 있다. 본 논문은 이를 해결하기 위해 선반입(prefetching)을 적용한 확장된 R-Tree인 PR-tree(Prefetching R-Tree)를 제안하고 평가하였다 PR-Tree는 펜-아웃을 증가시키고 트리의 높이를 낮추기 위해 실제 캐시 라인의 정수 배인 노드를 생성하고, 선반입을 적용하여 노드 캐시로 인한 메모리 지연을 최소화하였다. 또한 접근할 노드를 선반입하여 노드간 이동시 발생하는 캐시 실패도 최소화하였다. PR-Tree는 실험에서 R-Tree보다 검색 연산에서 최대 38%의 성능 향상을 보였으며, 갱신 연산에서도 최대 30%의 성능 향상을 보였다.

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Design and implementation of a time-based R-tree for indexing moving objects (이동체의 색인을 위한 시간 기반 R-트리의 설계 및 구현)

  • 전봉기;홍봉희
    • Journal of KIISE:Databases
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    • v.30 no.3
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    • pp.320-335
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    • 2003
  • Location-Based Services(LBS) give rise to location-based queries of which results depend on the locations of moving objects. One of important applications of LBS is to examine tracks of continuously moving objects. Moving objects databases need to provide 3-dimensional indexing for efficiently processing range queries on the movement of continuously changing positions. An extension of the 2-dimensional R-tree to include time dimension shows low space utilization and poor search performance, because of high overlap of index nodes and their dead space. To solve these problems, we propose a new R-tree based indexing technique, namely TR-tree. To increase storage utilization, we assign more entries to the past node by using the unbalanced splitting policy. If two nodes are highly overlapped, these nodes are forcibly merged. It is the forced merging policy that reduces the dead space and the overlap of nodes. Since big line segments can also affect the overlap of index nodes to be increased, big line segments should be clipped by the clipping policy when splitting overfull nodes. The TR-tree outperforms the 3DR-tree and TB-tree in all experiments. Particularly, the storage utilization of the TR-tree is higher than the R-tree and R*-tree.

Dynamic Cell Leveling to Support Location Based Queries in R-trees (R-tree에서 위치 기반 질의를 지원하기 위한 동적 셀 레벨링)

  • Jung, Yun-Wook;Ku, Kyong-I;Kim, Yoo-Sung
    • Journal of Korea Spatial Information System Society
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    • v.6 no.2 s.12
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    • pp.23-37
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    • 2004
  • Location Based Services(LBSs) in mobile environments become very popular recently. For efficient LBSs, spatial database management systems must need a spatial indexing scheme such as R-trees in order to manage the huge spatial database. However, it may need unnecessary disk accesses since it needs to access objects which are not actually concerned to user's location-based queries. In this paper, to support the location-based queries efficiently, we propose a CLR-tree(Cell Leveling R-tree) in which a dynamic cell is built up within the minimum bounding rectangle of R-trees' node. The cell level of nodes is compared with the query's cell level in location-based query processing and determines the minimum search space. Also, we propose the insertion, split, deletion, and search algorithms for CRL-trees. From the experimental results, we see that a CLR-tree is able to decrease $5{\sim}20%$ of disk accesses from those of R-trees. So, a CLR-tree can be used for fast accessing spatial objects to user's location-based queries in LBSs.

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A Study on Spatial-temporal indexing for querying current and past positions (현재와 과거 위치 질의를 위한 시공간 색인에 관한 연구)

  • Jun, Bong-Gi
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.6
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    • pp.1250-1256
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    • 2004
  • The movement of continuously changing positions should be stored and indexed for querying current and past positions. A simple extension of the original R-tree to add time as another dimension, called 3D R-tree, does not handle current position queries and does not address the problem of low space utilization due to high overlap of index nodes. In this paper, 1 propose the dynamic splitting policy for improving the 3D R-tree in order to improve space utilization of split nodes. 1 also extend the original 3D R-tree by introducing a new tagged index structure for being able to query the current and past positions of moving objects. 1 found out that my extension of the original R-tree, called the tagged dynamic 3DR-tree, outperforms both the 3D R-tree and 75-tree when querying current and past position.

An Efficient Parallel Construction Scheme of An R-Tree using Hadoop (Hadoop을 이용한 R-트리의 효율적인 병렬 구축 기법)

  • Cong, Viet-Ngu Huynh;Kim, Jongmin;Kwon, Oh-Heum;Song, Ha-Joo
    • Journal of Korea Multimedia Society
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    • v.22 no.2
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    • pp.231-241
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    • 2019
  • Bulk-loading an R-tree can be a good approach to build an efficient one. However, it takes a lot of time to bulk-load an R-tree for huge amount of data. In this paper, we propose a parallel R-tree construction scheme based on a Hadoop framework. The proposed scheme divides the data set into a number of partitions for which local R-trees are built in parallel via Map-Reduce operations. Then the local R-trees are merged into an global R-tree that covers the whole data set. While generating the partitions, it considers the spatial distribution of the data into account so that each partition has nearly equal amounts of data. Therefore, the proposed scheme gives an efficient index structure while reducing the construction time. Experimental tests show that the proposed scheme builds an R-tree more efficiently than the existing approaches.

A Hybrid Index based on Aggregation R-tree for Spatio-Temporal Aggregation (시공간 집계정보를 위한 Aggregation R-tree 기반의 하이브리드 인덱스)

  • You, Byeong-Seob;Bae, Hae-Young
    • Journal of KIISE:Databases
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    • v.33 no.5
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    • pp.463-475
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    • 2006
  • In applications such as a traffic management system, analysis using a spatial hierarchy of a spatial data warehouse and a simple aggregation is required. Over the past few years, several studies have been made on solution using a spatial index. Many studies have focused on using extended R-tree. But, because it just provides either the current aggregation or the total aggregation, decision support of traffic policy required historical analysis can not be provided. This paper proposes hybrid index based on extended aR-tree for the spatio-temporal aggregation. The proposed method supports a spatial hierarchy and the current aggregation by the R-tree. The sorted hash table using the time structure of the extended aR-tree provides a temporal hierarchy and a historical aggregation. Therefore, the proposed method supports an efficient decision support with spatio-temporal analysis and is Possible currently traffic analysis and determination of a traffic policy with historical analysis.

Extended R-Tree with Grid Filter for Efficient Filtering (효율적인 여과를 위한 그리드 필터를 갖는 R-Tree 의 확장)

  • 김재흥
    • Spatial Information Research
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    • v.8 no.1
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    • pp.155-170
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    • 2000
  • When we use R-Tree,a spatial index, to find objects matches some predicate, it often leads to an incorrect result of perform filtering step only with MBR. And , each candidates need to be inspected to conform if it really satisfies with given query, so called, 'refinement step'. In refinement step. we should perform disk I/O and expansive spatial operations which is the cause of increasing retrieval costs. Therefore, to minimize the number of candidate after filtering step, two-phase filtering methods were studied, but there was many problems such as inefficiency of filtering,maintenance of additional informations and reconstruction of data resulted from the loss of original information. So , in this paper, I propose an Extended R-Tree which provides ability to retrieve spatial objects only with some simple logical operations using Grid Table, truth table strong the information about the existence of spatial objects, in second filtering step. Consequently , this Extended R-Tree using Grid Filter has low cost of operation for filtering because of efficient second filtering step, and better filtering efficiency caused by high quality of approximation.

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Study on applying Quad-Tree & R-Tree for building the analysis system using massive ship position data (대용량 선박위치정보 분석시스템 구축을 위한 Quad-Tree 및 R-Tree 자료구조 적용에 대한 연구)

  • Lee, Sang-Jae;Park, Gyei-Kark;Kim, Do-Yeon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.6
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    • pp.698-704
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    • 2011
  • This study aims to facilitate and increase the performance of the Traffic Analysis System which receives the location information of vessels sailing along the coast all over the country in real time and analyzes the vessels' sailing situation. Especially, the research has a signification that the system is designed with the application of Quad-Tree and R-Tree data structure in order for system users to search necessary information quickly and effectively, and it verifies the improvement of the performance by showing experiment results comparing the existing Traffic Analysis System to newly upgraded Traffic Analysis System.