• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.718-720
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• 2008

In this paper, the study focus on continuous query in EPC Information Services(EPCIS) middleware which is a component of RFID system. We can consider EPCIS as a data stream system with a repository. In our work continuous query is implemented in two query execution model. One is standing query model another is traditional query execution model in which continuous query run over database periodically. Furthermore a balance strategy is presented. It is used to determine which continuous query implementation model is suitable for the query. Finally we conclude our work and issue some research topic for future work.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.285-290
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• 2004

Processing the continuous queries which perform the identical query in given time interval is required because of the continuous change of location of the moving object. Thus the continuous query may cause loads to the server or network and take the cost of processing time because the continuous query is performed in server as the moving object's location changes. In this paper, we propose the query processing technique to perform the continuous range query that is a sort of continuous query effectively The proposed query processing technique predicts the query result and the validity of query answer to perform the continuous query for reciprocal moving object. And it enables to process effectively the query that moves dynamically.

• ETRI Journal
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• v.29 no.5
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• pp.691-693
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• 2007

Existing methods to process continuous range queries are not scalable. In particular, as the number of continuous range queries on a large number of moving objects becomes larger, their performance degrades significantly. We propose a novel query indexing method called the projected attribute bit (PAB)-based query index. We project a two-dimensional continuous range query on each axis to get two one-dimensional bit lists. Since the queries are transformed to bit lists and query evaluation is performed by bit operations, the storage cost of indexing and query evaluation time are reduced significantly. Through various experiments, we show that our method outperforms the containment-encoded squares-based indexing method, which is one of the most recently proposed methods.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.3-5
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• 2007

Many continuous queries are important to be process efficiently in a data stream environment. It is applied a query index technique that takes linear performance irrespective of the number and width of intervals for processing many continuous queries. Previous researches are not able to support the dynamic insertion and deletion to arrange intervals for constructing an index previously. It shows that the insertion and search performance is slowed by the number and width of interval inserted. Many intervals have to be inserted and searched linearly in a data stream environment. Therefore, we propose Hashed Multiple Lists in order to process continuous queries linearly. Proposed technique shows fast linear search performance. It can be utilized the systems applying a sensor network, and preprocessing technique of spatiotemporal data mining.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.454-462
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• 2014

With the development of location aware technologies and mobile devices, location-based services have been studied. To provide location-based services, many researchers proposed methods for processing various query types with Mapreduce(MR). One of the proposed methods, is a Reverse k-nearest neighbor(RkNN) query processing method with MR. However, the existing methods spend too much cost to process the continuous RkNN query. In this paper, we propose an efficient continuous RkNN query processing method with MR to resolve the problems of the existing methods. The proposed method uses the 60-degree-pruning method. The proposed method does not need to reprocess the query for continuous query processing because the proposed method draws and monitors the monitoring area including the candidate objects of a RkNN query. In order to show the superiority of the proposed method, we compare it with the query processing performance of the existing method.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.6
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• pp.397-401
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• 2007

Recent applications on continuous queries on moving objects are extended quickly to various parts. These applications need not only 2-dimensional space data but also high-dimensional space data. If we use previous index for overlapped continuous range queries on high-dimensional space data, as the number of continuous range queries on a large number of moving objects becomes larger, their performance degrades significantly. We focus on stationary queries, non-exponential increase of storage cost and efficient processing time for large data sets. In this paper, to solve these problems, we present a novel query indexing method, denoted as PAB(Projected Attribute Bit)-based query index. We transfer information of high-dimensional continuous range query on each axis into one-dimensional bit lists by projecting technique. Also proposed query index supports incremental update for efficient query processing. Through various experiments, we show that our method outperforms the CES(containment-encoded squares)-based indexing method which is one of the most recent research.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.467-470
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• 2003

When user wants to find objects which have the nearest position from him, we use the nearest neighbor (NN) query. The GIS applications, such as navigation system and traffic control system, require processing of NN query for moving objects (MOs). MOs have trajectory with changing their position over time. Therefore, we should be able to find NN object continuously changing over the whole query time when process NN query for MOs, as well as moving nearby on trajectory of query. However, none of previous works consider trajectory information between objects. Therefore, we propose a method of continuous NN query for trajectory of MOs. We call this CTNN (continuous trajectory NN) technique. It ran find constantly valid NN object on the whole query time by considering of trajectory information.

• 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.

• Journal of KIISE:Databases
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• v.33 no.3
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• pp.310-326
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• 2006

In this paper, we deal with a method of efficiently processing continuous queries in a data stream environment. We classify previous query processing methods into two dual categories - data-initiative and query-initiative - depending on whether query processing is initiated by selecting a data element or a query. This classification stems from the fact that data and queries have been treated asymmetrically. For processing continuous queries, only data-initiative methods have traditionally been employed, and thus, the performance gain that could be obtained by query-initiative methods has been overlooked. To solve this problem, we focus on an observation that data and queries can be treated symmetrically. In this paper, we propose the duality model of data and queries and, based on this model, present a new viewpoint of transforming the continuous query processing problem to a multi-dimensional spatial join problem. We also present a continuous query processing algorithm based on spatial join, named Spatial Join CQ. Spatial Join CQ processes continuous queries by finding the pairs of overlapping regions from a set of data elements and a set of queries defined as regions in the multi-dimensional space. The algorithm achieves the effects of both of the two dual methods by using the spatial join, which is a symmetric operation. Experimental results show that the proposed algorithm outperforms earlier methods by up to 36 times for simple selection continuous queries and by up to 7 times for sliding window join continuous queries.

• The KIPS Transactions:PartD
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• v.14D no.3 s.113
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• pp.273-284
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• 2007

RFID middleware systems collect and filter the RFID streaming data gathered continuously by numerous readers in order to process requests from applications. These requests are called continuous queries because they are kept on executing during certain periods. To enhance the performance of the middleware, it is required to build an index to process the continuous queries efficiently. Several approaches of building an index on not data records but queries, called Query Index, are proposed and widely used for evaluating continuous queries over streaming data. The EPCglobal proposed an Event Cycle Specification (ECSpec) model, which is a standard query interface for RFID applications. Continuous queries based on ECSpec consist of a large number of segments for representing the query conditions. The problem with using any of the existing query indexes on these continuous queries is that it takes a long time to build the index because it is necessary to insert a large number of segments into the index. To solve this problem, we propose an Aggregate Transformation that converts a group of segments into a compressed data which is representative of the segments. We compare the performance of a transformed index with the existing query indexes.