• Journal of Communications and Networks
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• v.13 no.4
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• pp.400-407
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• 2011

Various air indexing and data scheduling schemes for wireless broadcast of spatial data have been developed for energy efficient query processing. The existing schemes are not effective when the clients' data access patterns are skewed to some items. It is because the schemes are based on flat broadcast that does not take the popularity of the data items into consideration. In this paper, thus, we propose a data scheduling scheme letting the popular items appear more frequently on the channel, and grid-based distributed index for non-flat broadcast (GDIN) for window query processing. The proposed GDIN allows quick and energy efficient processing of window query, matching the clients' linear channel access pattern and letting the clients access only the queried data items. The simulation results show that the proposed GDIN significantly outperforms the existing schemes in terms of access time, tuning time, and energy efficiency.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.113-115
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• 2000

A GIS software GEO Millennium SystemTM has been developed to integrated with spatial database that combines conventional and spatially related data. As we known well the standard query language lacks the support of spatial data type and predicate, and can not serve as the query language in the spatial database directly; some extended strategies have been proposed, but some of them need their own storage manager, some introfuce new clause into the SELECT-FROM-WHERE structure, and some is very complex and available to us. So we designed our own query language on the conventional storage manager system. It supports the Spatial Data Type and predicate, and provides the full query capabilities of SQL on the non-spatial part of the database while being tightly integrated with the spatial part, without changing the standard SQL structure.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.22-24
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• 2001

A new GIS software Spatial Database Engine(SDE) has been developed to integrated with spatial database that combines conventional and spatially related data. As we known well in the traditional relation database system, the query evaluation techniques are a well-researched subject, many useful and efficient algorithms have been proposed, but in the spatial database system, it is a litter difference with the traditionally ones. Based on the Query Graph Model(QGM), we implemented our own query evaulation plan in the SDE, which can deal with the full functionality query statement SELECT-FROM-WHERE_GROUPBY-HAVING, and treat the spatial data and non-spatial data seamlessly. We proposed a novel multi way join algorithm base on nest loop that may be attractive.

• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.45-56
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• 2010

This paper suggests constraint data modeling based on constraint data presentation techniques to perform complex spatial database operation naturally. We were able to identify the limitation of extendibility of dimension and non-equal framework via relevant research for former schema of spatial database and query processing. Therefore we described generalized tuple of spatial data and the definition of suggested constraint data modeling. Also we selected MLPQ/PReSTO tool among constraint database prototype and compare standard functionality of ARC/VIEW. Then we design scenario for spatial operation using MLPQ/PReSTO and we suggested application effect after query processing. Based on above explanation, we were able to identify that we can process spatial data naturally and effectively using simple constraint routine on same framework via constraint data modeling.

• 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.

• 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.6 no.2 s.12
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• pp.51-62
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• 2004

Recently, the location-based service for moving customers is becoming one of the most important service in mobile communication area. For moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. The primary processing of LBS application is spatio-temporal range queries. To improve the throughput of spatio-temporal range queries, the time of disk I/O in query processing should be reduced. In this paper, we adopt non-uniform two-level grid index structures of GALIS architecture,which are designed to minimize update operations. We propose query scheduling technique using spatial relationship and time relationship and a combined spatio-temporal query processing method using time zone concepts to improve the throughput of query processing. Some experimental results are shown for range queries with different query range to show the performance tradeoffs of the proposed methods.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.499-501
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• 2003

As semiconductor memory becomes cheaper, the memory capacity of computer system is increasing. Therefore computer system has sufficient memory for a plentiful spatial data. With emerging spatial application required high performance, this paper presents a GIS database system in main memory. Memory residence can provide both functionality and performance for a database management system. This paper describes design of DBMS for storing, querying, managing and analyzing for spatial and non-spatial data in main-memory. This memory resident GIS DBMS supports SQL for spatial query, spatial data model, spatial index and interface for GIS tool or applications.

• Journal of Korea Spatial Information System Society
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• v.1 no.2 s.2
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• pp.33-46
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• 1999

In distributed computing platforms like CORBA, wrappers are used to integrate heterogeneous systems or databases. A spatial data provider is one of the wrappers because it provides clients with uniform access interfaces to diverse data sources. The individual implementation of spatial data providers for each of different data sources is not efficient because of redundant coding of the wrapper modules. This paper presents a new architecture of the spatial data provider which consists of two layered objects : independent wrapper components and dependent wrapper components. Independent wrapper components would be reused for implementing a new data provider for a new data source, which dependent wrapper components should be newly coded for every data source. This paper furthermore discussed the issues of implementing the representation of query results in the middleware. There are two methods of keeping query results in the middleware. One is to keep query results as non-CORBA objects and the other is to transform query results into CORBA objects. The evaluation of the above two methods shows that the cost of making CORBA objects is very expensive.