• Title/Summary/Keyword: 공간 순서화 곡선

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A Multi-dimensional Range Query Processing using Space Filling Curves (공간 순서화 곡선을 이용한 다차원 영역 질의 처리)

  • Back, Hyun;Won, Jung-Im;Yoon, Jee-Hee
    • Journal of Korea Spatial Information System Society
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    • v.8 no.2 s.17
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    • pp.13-38
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    • 2006
  • Range query is one of the most important operations for spatial objects, it retrieves all spatial objects that overlap a given query region in multi-dimensional space. The DOT(DOuble Transformation) is known as an efficient indexing methods, it transforms the MBR of a spatial object into a single numeric value using a space filling curve, and stores the value in a $B^+$-tree. The DOT index is possible to be employed as a primary index for spatial objects. However, the range query processing based on the DOT index requires much overhead for spatial transformations to get the query region in the final space. Also, the detailed range query processing method for 2-dimensional spatial objects has not been studied yet in this paper, we propose an efficient multi-dimensional range query processing technique based on the DOT index. The proposed technique exploits the regularities in the moving patterns of space filling curves to divide a query region into a set of maximal sub-legions within which space filling curves traverse without interruption. Such division reduces the number of spatial transformations required to perform the range query and thus improves the performance of range query processing. A visual simulator is developed to show the evaluation method and the performance of our technique.

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An Efficient Spatial Join Method Using DOT Index (DOT 색인을 이용한 효율적인 공간 조인 기법)

  • Back, Hyun;Yoon, Jee-Hee;Won, Jung-Im;Park, Sang-Hyun
    • Journal of KIISE:Databases
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    • v.34 no.5
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    • pp.420-436
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    • 2007
  • The choice of an effective indexing method is crucial to guarantee the performance of the spatial join operator which is heavily used in geographical information systems. The $R^*$-tree based method is renowned as one of the most representative indexing methods. In this paper, we propose an efficient spatial join technique based on the DOT(Double Transformation) index, and compare it with the spatial Join technique based on the $R^*$-tree index. The DOT index transforms the MBR of an spatial object into a single numeric value using a space filling curve, and builds the $B^+$-tree from a set of numeric values transformed as such. The DOT index is possible to be employed as a primary index for spatial objects. The proposed spatial join technique exploits the regularities in the moving patterns of space filling curves to divide a query region into a set of maximal sub-regions within which space filling curves traverse without interruption. Such division reduces the number of spatial transformations required to perform the spatial join and thus improves the performance of join processing. The experiments with the data sets of various distributions and sizes revealed that the proposed join technique is up to three times faster than the spatial join method based on the $R^*$-tree index.

Spatial Partitioning using filbert Space Filling Curve for Spatial Query Optimization (공간 질의 최적화를 위한 힐버트 공간 순서화에 따른 공간 분할)

  • Whang, Whan-Kyu;Kim, Hyun-Guk
    • The KIPS Transactions:PartD
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    • v.11D no.1
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    • pp.23-30
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    • 2004
  • In order to approximate the spatial query result size we partition the input rectangles into subsets and estimate the query result size based on the partitioned spatial area. In this paper we examine query result size estimation in skewed data. We examine the existing spatial partitioning techniques such as equi-area and equi-count partitioning, which are analogous to the equi-width and equi-height histograms used in relational databases, and examine the other partitioning techniques based on spatial indexing. In this paper we propose a new spatial partitioning technique based on the Hilbert space filling curve. We present a detailed experimental evaluation comparing the proposed technique and the existing techniques using synthetic as well as real-life datasets. The experiments showed that the proposed partitioning technique based on the Hilbert space filling curve achieves better query result size estimation than the existing techniques for space query size, bucket numbers, skewed data, and spatial data size.

A Distributed Spatial Indexing Technique based on Hilbert Curve and MBR for k-NN Query Processing in a Single Broadcast Channel Environment (단일방송채널환경에서 k-최근접질의 처리를 위한 힐버트 곡선과 최소영역 사각형 기반의 분산 공간 인덱싱 기법)

  • Yi, Jung-Hyung;Jung, Sung-Won
    • Journal of KIISE:Databases
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    • v.37 no.4
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    • pp.203-208
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    • 2010
  • This paper deals with an efficient index scheduling technique based on Hilbert curve and MBR for k-NN query in a single wireless broadcast channel environment. Previous works have two major problems. One is that they need a long time to process queries due to the back-tracking problem. The other is that they have to download too many spatial data since they can not reduce search space rapidly. Our proposed method broadcasts spatial data based on Hilbert curve order where a distributed index table is also broadcast with each spatial data. Each entry of index table represents the MBR which groups spatial data. By predicting the unknown location of spatial data, our proposed index scheme allows mobile clients to remove unnecessary data and to reduce search space rapidly. As a result, our method gives the decreased tuning time and access latency.

Spatio-Temporal Data Warehouses Using Fractals (프랙탈을 이용한 시공간 데이터웨어하우스)

  • 최원익;이석호
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10b
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    • pp.46-48
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    • 2003
  • 최근 시공간 데이타에 대한 OLAP연산 효율을 증가시키기 위한 여러 가지 연구들이 행하여지고 있다. 이들 연구의 대부분은 다중트리구조에 기반하고 있다. 다중트리구조는 공간차원을 색인하기 위한 하나의 R-tree와 시간차원을 색인하기 위한 다수의 B-tree로 이루어져 있다. 하지만, 이러한 다중트리구조는 높은 유지비용과 불충분한 질의 처리 효율로 인해 현실적으로 시공간 OLAP연산에 적용하기에는 어려운 점이 있다. 본 논문에서는 이러한 문제를 근본적으로 개선하기 위한 접근 방법으로서 힐버트큐브(Hilbert Cube, H-Cube)를 제안하고 있다. H-Cube는 집계질의(aggregation query) 처리 효율을 높이기 위해 힐버트 곡선을 이용하여 셀들에게 완전순서(total-order)를 부여하고 있으며, 아울러 전통적인 누적합(prefix-sum) 기법을 함께 적용하고 있다. H-Cube는 적응적이며, 완전순서화되어 있으며, 또한 누적합을 이용한 셀 기반의 색인구조이다. 본 논문에서는 H-Cube의 성능 평가를 위해서 다양한 실험을 하였으며, 그 결과로서 유지비용과 질의 처리 효율성면 모두에서 다중트리구조보다 높은 성능 향상이 있음을 보인다.

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Virtual Cell based $B^+$-tree Index Structure of Moving Objects for Location Based Services (위치 기반 서비스를 위한 가상 셀 기반 $B^+$-tree 이동객체 색인 기법)

  • Park, Yong-Hun;Seo, Dong-Min;Song, Seok-Il;Yoo, Jae-Soo
    • Proceedings of the Korean Information Science Society Conference
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    • 2010.06c
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    • pp.185-190
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    • 2010
  • 최근 위치 인식 기술과 휴대 장치의 발달로 인해 이동하는 객체를 기반으로 하는 위치 기반 서비스(Location Based Service, LBS)의 관심이 점점 증가하고 있고 그에 관련된 연구들이 활발하게 진행되고 있다. 이동 객체의 응용은 빈번하게 변경되는 이동객체의 위치정보를 효과적으로 처리할 수 있는 색인구조를 필요로 한다. 위치정보를 색인하기 위해 R-tree 기반의 색인들이 제안되었다. 하지만 R-tree는 변경보다는 검색 연산에 초점이 맞추어진 색인구조이기 때문에 잦은 변경을 다루어야 하는 이동객체 환경에 적합하지 못하다. 최근 이러한 객체의 빠른 위치 변경을 지원하는 그리드 기반의 색인 구조가 제안되었다. 하지만 셀의 객체 점유율에 따라 검색 속도가 저하되는 단점은 여전히 해결되지 못하고 있다. 이러한 단점은 객체들이 특정 영역에 몰리는 경우 또는 그리드의 해상도를 잘못 지정한 경우 더욱 부각된다. 본 논문에서는 이러한 단점을 해결하기 위해 가상 셀 기반의 색인 구조를 제안한다. 데이터 페이지에 객체의 점유율을 보장하기 위해 여러 개의 인접한 셀들의 데이터를 한 데이터 페이지에 함께 저장한다. 공간 채움 곡선을 기반으로 순서화된 셀들로 셀의 인접성을 결정한다. 또한 공간 채움 곡선의 차수를 동적으로 지정하여 객체가 집중된 셀에 대해서는 셀의 단위 크기를 작게 지정한다. 뿐만 아니라 셀을 표현하기 위한 식별자를 위해 비트를 이용한 표현식을 제안하였다. 이로 인해 노드의 팬아웃을 증가시켰고, 저장공간을 절약하였다. 실험을 통해서 제안하는 색인 기법의 우수성을 증명하였다.

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Hilbert Cube for Spatio-Temporal Data Warehouses (시공간 데이타웨어하우스를 위한 힐버트큐브)

  • 최원익;이석호
    • Journal of KIISE:Databases
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    • v.30 no.5
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    • pp.451-463
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    • 2003
  • Recently, there have been various research efforts to develop strategies for accelerating OLAP operations on huge amounts of spatio-temporal data. Most of the work is based on multi-tree structures which consist of a single R-tree variant for spatial dimension and numerous B-trees for temporal dimension. The multi~tree based frameworks, however, are hardly applicable to spatio-temporal OLAP in practice, due mainly to high management cost and low query efficiency. To overcome the limitations of such multi-tree based frameworks, we propose a new approach called Hilbert Cube(H-Cube), which employs fractals in order to impose a total-order on cells. In addition, the H-Cube takes advantage of the traditional Prefix-sum approach to improve Query efficiency significantly. The H-Cube partitions an embedding space into a set of cells which are clustered on disk by Hilbert ordering, and then composes a cube by arranging the grid cells in a chronological order. The H-Cube refines cells adaptively to handle regional data skew, which may change its locations over time. The H-Cube is an adaptive, total-ordered and prefix-summed cube for spatio-temporal data warehouses. Our approach focuses on indexing dynamic point objects in static spatial dimensions. Through the extensive performance studies, we observed that The H-Cube consumed at most 20% of the space required by multi-tree based frameworks, and achieved higher query performance compared with multi-tree structures.

Spatial Distribution and Dynamics of Vegetation on a Gravel Bar: Case Study in the Bangtae Stream (자갈 하중주에서 식생의 공간 분포 및 동태: 방태천의 사례)

  • Pee, Jung-Hun;Kim, Hye-Soo;Kim, Gyung-Soon;Oh, Woo-Seok;Koo, Bon-Yoel;Lee, Chang-Seok
    • Korean Journal of Ecology and Environment
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    • v.46 no.2
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    • pp.215-224
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    • 2013
  • We clarified the background for establishment of vegetation by comparing the spatial distribution maps of vegetation and substrate on a gravel bar in the Bangtae stream located on Inje-gun of Gangwon-do, the central eastern Korea. The total vegetation coverage was higher in the interior and lower in the marginal parts of the gravel bar. Spatial distribution of vegetation on the longitudinal section of the gravel bar tended to be arranged in the order of shrub, subtree, and tree dominated vegetation types from the front (upstream) toward the rear (downstream) parts. Coverage of the herbaceous plants was higher in the central and rear parts and lower in the front and right parts of the gravel bar. Vegetation height was higher in the rear part and became lowered as move toward the front part. Substrate was distributed in the order of boulder, gravel, sand, and boulder from the front toward the rear parts. Ordination of stands based on vegetation data was arranged in the order of annual plant, perennial herb, shrub, and tree dominated vegetation as move from the right to the left parts on the axis I. Species richness was higher in the order of Pinus densiflora community, Phragmites japonica community, Salix gracilistyla community, Fraxinus rhynchophylla community, annual plant dominated vegetation, and Prunus padus for. padus community based on the species rank-abundance curve. The order based on the Shannon's index was some different; diversity of Phragmites japonica community and Salix gracilistyla community, which showed higher dominance degree, were low differently from species richness. In conclusion, it was evaluated that the gravel bar newly established toward the upstream and vegetation dynamics of the gravel bar seemed to follow ecosystem mechanisms of succession. As were shown in the above results, the Bangtae stream corresponded to the upstream and thereby particle size of substrate was big. Therefore, they move by rolling and are accumulated for the upstream. Vegetation types were arranged in the order of woodland, shrub-land and grassland from the rear toward the front parts of the gravel bar and thereby reflected the formation process of the bar. However, the gravel bar is disturbed frequently by not only the running water but also the suspended sand as the dynamic space. Such disturbances cause habitat diversity and consequently led to high biodiversity.