• Journal of KIISE:Databases
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• v.36 no.4
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• pp.314-320
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• 2009

Skyline queries have recently received considerable attention in the searching services. The skyline contains interesting objects that are not dominated by any other objects on all dimensions. Many related works have processed a skyline on static data or on moving objects in Euclidean space. However, this paper assumes that the point of a skyline query continuously moves in road networks. We propose a new method that efficiently processes continuous skyline queries in road networks through pre-computed shortest range data of objects. Our experiments show that the proposed method is about 100 times faster than previous methods in terms of query processing time.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.70-75
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• 2015

In this paper, we explore the efficient processing of continuous range queries over a huge number of moving objects, each of which retrieves the moving objects that are currently located within a geographic query region of interest. The moving objects should continually communicate with the server to report their current locations, so as to keep the results of the continuous range queries up-to-date. However, this increases the server workload and involves a enormous amount of communication as the number of continuous range queries and the moving objects becomes enormous. In this paper, we adopt an approach where we leverage available memory and computational resources of the moving objects in order to resolve these problems. To this end, we propose a query indexing structure, referred to as the Space Partitioning Query Index(SPQI), which enables the server to efficiently cooperate with the moving objects for processing continuous range queries. SPQI improves system performance in terms of server workload and communication cost. Through simulations, we show the superiority of SPQI.

• Journal of KIISE:Databases
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• v.31 no.5
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• pp.492-504
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• 2004

Recently, as growing of interest for LBS(location-based services) techniques, lots of works on moving objects that continuously change their information over time, have been performed briskly. Also, researches for NN(nearest neighbor) query which has often been used in LBS, are progressed variously However, the results of conventional NN Query processing techniques may be invalidated as the query and data objects move. Therefore, they are usually meaningless in moving object management system such as LBS. To solve these problems, in this paper we propose a new nearest neighbor query processing technique, called CTNN, which is possible to meet accurate and continuous query processing for moving objects. Our techniques include an Approximate CTNN(ACTNN) technique, which has quick response time, and an Exact CTNN(ECTNN) technique, which makes it possible to search nearest neighbor objects accurately. In order to evaluate the proposed techniques, we experimented with various datasets. Experimental results showed that the ECTNN technique has high accuracy, but has a little low performance for response time. Also the ACTNN technique has low accuracy comparing with the ECTNN, but has quick response time The proposed techniques can be applied to navigation system, traffic control system, distribution information system, etc., and specially are most suitable when both data and query are moving objects and when we already know their trajectory.

• 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.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.47-58
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• 2012

In this paper, we propose a continuous k-nearest neighborhood query processing method for updating the query results in real-time over mobile peer-to-peer environments. The proposed method disseminates a monitoring region to efficiently monitor the k-nearest neighbor peers. The Monitoring Region is created to assure at least k peers as the result of the query within the time range using the vector of neighbor peers. In the propose method, the monitoring region is valid for a long time because it is calculated by the vector of neighbor peers of the query peer. Therefore, the proposed method decreases the cost of re-processing by monitoring region invalidation. In order to show the superiority of the proposed method, we compare it with the previous schemes through performance evaluation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2224-2229
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• 2012

Since sensor data are inserted into a data set continuously, continuous queries should be evaluated for searching data. To processing the continuous queries, it is required to build a query index on each sensor node and to transmit result data appropriate for query predicates. However, if query predicates are transferred to all sensor nodes, massive messages are required. In this paper, we propose the node decision scheme using the sensor node decision tree in order to diminish messages. The entry of a leaf node in the node decision tree represents a sensor node and defines the data region of the sensor node. When a user query is issued, sensor nodes are decided by intersecting between data regions of the tree with the query predicates of the user query, and then the query predicates are transmitted to the selected sensor nodes. We also implement the proposed sensor node decision tree and evaluate the experiments for the tree.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.4
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• pp.1-12
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• 2009

An RFID application needs to collect product's information scattered over the RFID network efficiently according to the globalization of RFID applied enterprises. To be informed of the stock status of products promptly in the supply chain network, especially, it is necessary to support queries that retrieve statistical information of tagged products. Since existing RFID network does not provide these kinds of queries, however, an application should request a query to several RFID middleware systems and analyze collected data directly. This process makes an application do a heavy computation for retrieving statistical information. To solve this problem, we define a new Distributed Continuous Query that finds information of tagged products from the global RFID network and provides statistical information to RFID applications. We also propose a Distributed Continuous Query System to process the distributed continuous query efficiently. To find out the movement of products via multiple RFID systems in real time, our proposed system uses Pedigree which represents trade information of items. Our system can also reduce the cost of query processing for removing duplicated data from multiple middleware systems by using Pedigree.

• International Journal of Internet, Broadcasting and Communication
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• v.5 no.2
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• pp.1-4
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• 2013

With the recent development of the ubiquitous computing technology, there are increasing interest and research in technologies such as sensors and RFID related to information recognition and location positioning in various ubiquitous fields. Especially, RTLS (Real-Time Locating Services) dealing with spatio-temporal data is emerging as a promising technology. For these reasons, the ISO/IEC published RTLS standard specification for compatibility and interoperability in RTLS. Therefore, in this paper, we designed and implemented Spatio-temporal Query Processing Systems for efficiently managing and searching the incoming Spatio-temporal data stream of moving objects. Spatio-temporal Query Processing Systems's spatio-temporal middleware maintains interoperability among heterogeneous devices and guarantees data integrity in query processing through real time processing of unceasing spatio-temporal data streams and two way synchronization of spatio-temporal DBMSs. Web Server uses the SOAP(Simple Object Access Protocol) message between client and server for interoperability and translates client's SOAP message into CQL(Continuous Query Language) of the spatio-temporal middleware.

• Journal of Korea Spatial Information System Society
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• v.11 no.3
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• pp.9-18
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• 2009

Recently, due to the advanced technologies of mobile devices and wireless communication, there are many studies on telematics and LBS(location-based service) applications. because moving objects usually move on spatial networks, their locations are updated frequently, leading to the degradation of retrieval performance. To manage the frequent updates of moving objects' locations in an efficient way, a new distributed grid scheme, called DS-GRID (distributed S-GRID), and k-NN(k-nearest neighbor) query processing algorithm was proposed[1]. However, the result of k-NN query processing technique may be invalidated as the location of query and moving objects are changed. Therefore, it is necessary to study on continuous k-NN query processing algorithm. In this paper, we propose both MCE-CKNN and MBP(Monitoring in Border Point)-CKNN algorithmss are S-GRID. The MCE-CKNN algorithm splits a query route into sub-routes based on cell and seproves retrieval performance by processing query in parallel way by. In addition, the MBP-CKNN algorithm stores POIs from the border points of each grid cells and seproves retrieval performance by decreasing the number of accesses to the adjacent cells. Finally, it is shown from the performance analysis that our CKNN algorithms achieves 15-53% better retrieval performance than the Kolahdouzan's algorithm.

• Journal of Internet Computing and Services
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• v.13 no.3
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• pp.93-105
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• 2012

A data stream is a series of tuples which are generated in real-time, incessant, immense, and volatile manner. As new information technologies are actively emerging, stream processing methods are being needed to efficiently handle data streams. Especially, finding out an efficient evaluation for a multi-way join would make outstanding contributions toward improving the performance of a data stream management system because a join operation is one of the most resource-consuming operators for evaluating queries. In this paper, in order to evaluate efficiently a multi-way join continuous query, we propose a novel method to decrease the cost of a query by eliminating unsuccessful intermediate results. For this, we propose a matrix-based structure for monitoring data streams and estimate the number of final result tuples of the query and find out unsuccessful tuples by matrix multiplication operations. And then using these information, we process efficiently a multi-way join continuous query by filtering out the unsuccessful tuples in advance before actual evaluation of the query.