• Journal of Digital Contents Society
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• v.8 no.4
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• pp.541-546
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• 2007

Traditional query processing method is not efficient for continuous queries with large continuous stream data. This paper proposes a data-driven query processing method for stream data. The structure of query plan and query execution method are presented. With the proposed method, multiple query processing and sharing among queries can be achieved. Also query execution time can be reduced by storing partial results of query execution. This paper showed an example of query processing with XML data and XQuery query.

• 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 Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1166-1176
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• 1999

The spationtemporal databases support a historical informations as well as spatial managements for various kinds of objects in the real world, and can be efficiently used in many applications such as geographic information system, urban plan system, car navigation system. However it is difficult to represent efficiently historical operations with conventional database query language for spatial objects. In terms of cost for query processing, it also degenerates performance of query processing because of syntactic limitations which is innate in conventional query representation. So in this paper, we introduce a new query language, entitled as STQL, which has been extended on the basis of the most popular relational database query language SQL. And we implement as well as evaluate a spationtemporal query processing system that get a query written by STQL and then process it in a main memory.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.113-122
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• 2008

In RFID system, Middleware collects and filters streaming data gathered continuously from readers to process applications requests. The enormous amount of data makes middleware in highly overloaded. Hence, we propose reader level filtering in order to reduce overall middleware load. In this paper, we consider reader filtering capability and define query plan to minimize number of queries for processing into middleware and reader level. We design and implement middleware system based on proposed query plan. We perform several experiments on implemented system. Our experiments show that the proposed query plan considerably improves the performance of middleware by diminishing processing time and network traffic between reader and middleware.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2467-2478
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• 1998

The spatiotemporal databases support historical informations as well as spatial managements for the objects in the real world, and can be efficiently used to various applications such as geographic information system, urban plan system, car navigation system. Although there are so far several pioneering works in spatioemporal data modeling, it is little to study on spatiotemporal query language. So in this paper, we at first survey a modeling technique that makes spatiotemporal objects into databases, and then show some sighificant functions supported by query language. Also we suggest a new spatiotemporal database query language, entitled as STQL, which make users to enable to manage efficient historical information as well as spatial management function on the basis of relational query language, SQL. Also the proposed STQL, shows their operationsl in spatiotemporal daabases.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.116-124
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• 2011

In this paper, We implemented vessel USN middleware by server-side method considering characteristics of ocean environment. We designed multiple query process module in order to efficient process multidimensional sensor stream data and proposed optimized query plan using Mjoin query and hash table. This paper proposed method that context aware of vessel and manage considering characteristics of ocean. We decided to risk context using SVM algorithm in context awareness management module. As a result, we obtained about 87.5% average accuracy for fire case and about 85.1% average accuracy for vessel risk case by input 5,000 data sets and implemented vessel USN monitoring system.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.220-230
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• 2013

In recent years, progress in hardware technology has resulted in the possibility of monitoring many events in real time. The volume of incoming data may be so large, that monitoring all individual data might be intractable. Revisiting any particular record can also be impossible in this environment. Therefore, many database schemes, such as aggregation, join, frequent pattern mining, and indexing, become more challenging in this context. This paper surveys the previous efforts to resolve these issues in processing data streams. The emphasis is on specifying and processing sliding window queries, which are supported in many stream processing engines. We also review the related work on stream query processing, including synopsis structures, plan sharing, operator scheduling, load shedding, and disorder control.

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.347-364
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• 1998

Oracle's KM Technology ㆍCore Technologies - Oracle Application Server 4.0 JCORBA Cartridge, JTS - Oracle 8.1 JavaVM, Java Stored Procedure, CORBA/ORB, IIOP - ConText Carridge 8.1 - Enterprise Scalability and Performance - Open SQL Query Layer - Fully-Extensible Object Model for custom solutions ㆍNext Plan - Oracle Application Server 4.1 EJB Cartridge(omitted)

• Journal of KIISE:Databases
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• v.32 no.5
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• pp.473-486
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• 2005

The Hippocratic database model recently proposed by Agrawal et at. incorporates privacy protection capabilities into relational databases. The authors have subsequenty proposed the Hippocratic XML daかabase model[4], an extension of the Hippocratic database model for XML databases. In this paper, we propose a new concept that we cail the dynamic predicate(DP) for effective access control in the Hippocratic XML database model. A DP is a novel concept that represents a dynamically constructed rendition that tan be adapted for determining the accessibility of elements during query execution. DPs allow us to effectively integrate authorization checking into the query plan so that unauthorized elements are excluded in the process of query execution. Using synthetic and real data, we have performed extensive experiments comparing query processing time with those of existing access control mechanisms. The results show that the proposed access control mechanism improves the wall clock time by up to 219 times over the top-down access control strategy and by up to 499 times over the bottom-up access control strategy. The major contribution of our, paper is enabling effective integration of access control mechanisms with the query plan using the DP under the Hippocratic XML database model.

• The KIPS Transactions:PartD
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• v.10D no.6
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• pp.927-934
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• 2003

Database query optimates the selectivety of a query to find the most efficient access plan. Multi-dimensional selectivity estimation technique is required for a query with multiple attributes because the attributes are not independent each other. Histogram is practically used in most commercial database products because it approximates data distributions with small overhead and small error rates. However, histogram is inadequate for a query with multiple attributes because it incurs high storage overhead and high error rates. In this paper, we propose a novel method for multi-dimentional selectivity estimation. Compressed information from a large number of small-sized histogram buckets is maintained using the discrete cosine transform. This enables low error rates and low storage overheads even in high dimensions. Extensive experimental results show adventages of the proposed approach.