• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.56-61
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• 2006

최근 공간 네트워크 데이터베이스를 위한 질의처리 알고리즘에 관한 연구가 많이 진행되어 왔다. 그러나 현재 좌표-기반 질의에 대한 연구는 활발히 진행중인 반면, 경로-기반 질의에 대한 연구는 매우 미흡한 실정이다. 공간 네트워크 데이터베이스에서는 이동객체가 공간 네트워크상에서만 이동하기 때문에 경로-기반 질의의 유용성이 매우 증대되므로, 경로-기반 질의에 대한 효율적인 질의처리 알고리즘 연구가 필수적이다. 따라서 본 논문에서는 경로-기반 질의의 대표적인 방법인 In-Route Nearest Neighbor 질의처리 알고리즘을 분석하여 기존 연구에서 고려하지 않은 시간 및 공간제약을 고려한 경로-기반 질의처리 알고리즘을 설계한다.

• Spatial Information Research
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• v.21 no.2
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• pp.23-33
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• 2013

W ith the recent advancement of IoT (Internet of Things) technology, there has been much interest in the spatial query processing which energy-efficiently acquires sensor readings from sensor nodes inside specified geographical area of interests. Therefore, various kinds of spatial query processing algorithms and distributed spatial indexing methods have been proposed. They can minimize energy consumption of sensor nodes by reducing wireless communication among them using in-network spatial filtering technology. However, they cannot optimize multiple spatial queries which w ill be w idely used in IoT, because most of them have focused on a single spatial query optimization. Therefore, we propose a new multiple spatial query optimization algorithm which can energy-efficiently process multiple spatial queries in a sensor network. The algorithm uses a concept of 'query merging' that performs the merged set after merging multiple spatial queries located at adjacent area. Here, our algorithm makes a decision on which is better between the merged and the separate execution of queries. For such the decision making, we additionally propose the cost estimation method on the spatial query execution. Finally, we analyze and clarify our algorithm's distinguished features using the spatial indexing methods of GR-tree, SPIX, CPS.

• Journal of Korea Spatial Information System Society
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• v.1 no.2 s.2
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• pp.137-149
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• 1999

Spatial database systems in client-server environment have network overload due to the large amount of spatial data transmission. Users use the window query that loads partial region of a whole map for quick response time in the environment. A series of window query such as screen movement, enlargement or shrinkage requires data in similar region and this increases network overload by re-transmitting the same data in intersected region with the earlier transmitted region. Removing the transmitted data from query results can solve this problem. In this paper, we design and implement a spatial object manager in order to remove the intersected region occurred by a series of window query. The spatial object manager manages the object identifiers of transmitted objects and removes transmitted objects from spatial objects of the query result by using the removal technique of the intersected region for the transmission and comparison. We utilize GEOMania Millennium server, an open client-server spatial database system, as spatial object manager in this paper. The result of the performance evaluation shows that the spatial object manager removes the transmission of the data redundancy, reduces network overload and improves the overall system performance.

• Spatial Information Research
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• v.19 no.1
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• pp.93-105
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• 2011

In recent years, large and complex three-dimensional building has been constructed by the development of building technology and advanced IT skills, and people have lived there and spent a considerable time so far. Accordingly. in this sophisticatcd three-dimensional space, emergencies services or convenient information services have been in demand. In order to provide these services efficiently, understanding of topological relationships among the complex space should be supported naturally. Not on1y each method of understanding the topological relationships but also its efficiency can be different depending on different topological data models. B-rep based data model is the most widely used for storaging and representing of topological relationships. And from early 2000s, many researches on a network based topological data model have been conducted. The purpose of this study is to verify the efficiency of performance on spatial queries. As a result, Network-based topological data model is more efficient than B-rep based data model for determining the spatial relationship.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.377-386
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• 2001

In spatial database system, spatial view is supported for efficient access method to spatial database and is managed by materialization and non-materialization technique. In non-materialization technique, repeated execution on the same query makes problems such as the bottle-neck effect of server-side and overloads on a network. In materialization technique, view maintenance technique is very difficult and maintenance cost is too high when the base table has been changed. In this paper, the SVMT (Spatial View Materialization Technique) is proposed by using R-tree re-construction. The SVMT is a technique which constructs a spatial index according to the distribution ratio of objects in spatial view. This ratio is computed by using a SVHR (Spatial View Height in R-tree) and SVOC (Spatial View Object Count). If the ratio is higher than the average, a spatial view is materialized and the R-tree index is re-used. In this case, the root node of this index is exchanged a node which has a MBR (Minimum Boundary Rectangle) value that can contains the whole region of spatial view at a minimum size. Otherwise, a spatial view is materialized and the R-tree is re-constructed. In this technique, the information of spatial view is managed by using a SVIT (Spatial View Information Table) and is stored on the record of this table. The proposed technique increases the speed of response time through fast query processing on a materialized view and eliminates additional costs occurred from repeatable query modification on the same query. With these advantages, it can greatly minimize the network overloads and the bottle-neck effect on the server.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.1-18
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• 2008

Because we can usually get many information through analyzing trajectories of moving objects on spatial networks, efficient trajectory index structures are required to achieve good retrieval performance on their trajectories. However, there has been little research on trajectory index structures for spatial networks such as FNR-tree and MON-tree. Also, because FNR-tree and MON-tree store the segment unit of moving objects, they can't support the trajectory of whole moving objects. In this paper, we propose an efficient trajectory index structures based on signatures on a spatial network, named SigMO-Tree. For this, we divide moving object data into spatial and temporal attributes, and design an index structure which supports not only range query but trajectory query by preserving the whole trajectory of moving objects. In addition, we divide user queries into trajectory query based on spatio-temporal area and similar-tralectory query, and propose query processing algorithms to support them. The algorithm uses a signature file in order to retrieve candidate trajectories efficiently Finally, we show from our performance analysis that our trajectory index structure outperforms the existing index structures like FNR-Tree and MON-Tree.

• Journal of Korea Spatial Information System Society
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• v.10 no.1
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• pp.15-28
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• 2008

In ubiquitous sensor networks(USN) environment, it is essential to process region query for user-demand services. Using R-tree is a preferred technique to process region query for in-network query environment. In USN environment, USN middleware must select sensors that transfers region query with accuracy because the lifetime of sensors is that of whole sensor networks. When R-tree is used, however, it blindly passes the region query including non-existent sensors where MBR(Minimum Boundary Rectangle) of R-tree is Intersected by region of query. To solve in this problem, we propose a reconstruction of region query method which is a trie-structured Quad tree in the base station that includes sensors in region of query select with accuracy. We observed that the proposed method delays response time than R-tree, but is useful for reducing communication cost and energy consumption.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.11-19
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• 2008

Recently, advances in mobile devices and wireless communication technologies require research on various location-based services. As a result, many studies on processing k-nearest neighbor query, which is most im portant one in location-based services, have been done. Most of existing studies use pre-computation technique to improve retrieval performance by computing network distance between POIs and nodes beforehand in spatial networks. However, they have a drawback that they can not deal with effectively the update of POIs to be searched. In this paper, we propose a distributed grid scheme using S-GRID to overcome the disadvantage of the existing work as well as to manage the location information of a large number of moving objects in efficient way. In addition, we describe a k-nearest neighbor(k-NN) query processing algorithm for the proposed distributed grid scheme. Finally, we show the efficiency of our distributed grid scheme by making a performance comparison between the k-NN query processing algorithm of our scheme and that of S-GRID.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5042-5048
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• 2010

In ubiquitous environments, many continuous query processing techniques make use of operator network and sharing methods on continuous data stream generated from various sensors. Since similar continuous queries with the location information intensively occur in specific regions, we suggest a new operator sharing method based on grid partition for the spatial continuous query processing for location-based applications. Due to the proposed method shares moving objects by the given grid cell without sharing spatial operators individually, our approach can not only share spatial operators including similar conditions, but also increase the query processing performance and the utilization of memory by reducing the frequency of use of spatial operators.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.879-888
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• 2006

Recently many researchers have focused on management of Historical trajectories of moving objects in Euclidean spaces due to numerous sizes of accumulated data over time. However, the movement of moving objects in real applications generally has some constraints, for example vehicles on roads can only travel along connected road networks. In this paper, we propose an indexing method for trajectories of moving objects on road networks in order to process the network-based spatiotemporal range query. Our method contains the connect information of road networks to use the network distance for query processing, deals with trajectories which are represented by road segments in road networks, and manages them using multiple R-trees assigned per each road segment. Furthermore, it has a structure to be able to share R-tree among several road segments in large road networks. Consequently, we show that our method takes about 30% less in node accesses for the network-based spatiotemporal range query processing than other methods based on the Euclidean distance by experiments.