• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.35-40
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• 2005

Recently, the location based service for moving customers is becoming one of the most important service in mobile communication area and 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 and 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 structure, 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.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.30-42
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• 2015

In this paper, we propose a new skyline query processing scheme to enhance accuracy of query processing and communication cost in mobile P2P environments. The proposed scheme consists of three stages such as the pre-skyline processing, the query transmission range extension policy, and the continuous skyline query processing. In the pre-skyline processing, a peer selects the candidate filtering objects who have the potential to be selected. By doing so, the proposed scheme reduces the filtering cost when processing the query. In the query transmission range extension policy, we have improved the accuracy by extending the query transmission range. In addition, it can handle continuous skyline query by performing the monitoring after the first skyline query processing. In order to show the superiority of the proposed method, we compare it with the existing schemes through performance evaluation. As a result, it was shown that the proposed scheme outperforms the existing schemes.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.294-297
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• 2005

Time series are comprehensively appeared and developed in many applications, ranging from science and technology to business and entertainrilent. Similarity search under time warping has attracted much interest between the time series in the large sequence databases. DTW (Dynamic Time Warping) is a robust distance measure and is superior to Euclidean distance for time series, allowing similarity matching although one of the sequences can elastic shift along the time axis. Nevertheless, it is more unfortunate that DTW has a quadratic time. Simultaneously the false dismissals are come forth since DTW distance does not satisfy the triangular inequality. In this paper, we propose an efficient range query algorithmbased on a new similarity search method under time warping. When our range query applies for this method, it can remove the significant non-qualify time series as early as possible before computing the accuracy DTW distance. Hence, it speeds up the calculation time and reduces the number of scanning the time series. Guaranteeing no false dismissals, the lower bounding function is advised that consistently underestimate the DTW distance and satisfy the triangular inequality. Through the experimental result, our range query algorithm outperforms the existing others.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.132-139
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• 2004

A range $Top-\kappa$ query returns top k records in order of a measure attribute within a specified region on multi-dimensional data, and it is a powerful tool for analysis in spatial databases and data warehouse environments. In this paper, we propose an algorithm for answering the query via selective traverse of a Hierarchical Max R-Tree(HMR-tree). It is possible to execute the query by accessing only a small part of the leaf nodes in the query region, and the query performance is nearly constant regardless of the size of the query region. The algorithm manages the priority queue efficiently to reduce cost of handling the queue and the proposed HMR-tree can guarantee the same fan-out as the original R-tree.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.715-725
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• 2020

In this paper, we propose an optimization scheme for a k-Nearest Neighbor(k-NN) query, which finds k objects closest to the query in the high dimensional feature vectors. The k-NN query is converted and processed into a range query based on the range that is likely to contain k data. In this paper, we propose an optimization scheme using DNN model to derive an optimal range that can reduce processing cost and accelerate search speed. The entire system of the proposed scheme is composed of online and offline modules. In the online module, a query is actually processed when it is issued from a client. In the offline module, an optimal range is derived for the query by using the DNN model and is delivered to the online module. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1095-1101
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• 2012

As the amount of data increases explosively, a large scale database system is emerged to store, retrieve and manipulate it. There are several issues in this environments such as, consistency, availability and fault tolerance. In this paper, we address a efficient range-query method where data management services are separated from transaction management services in large-scale database systems. A study had been proposed using partitions to protect independence of two modules and to resolve the phantom problem, but this method was efficient only when range-query is specified by a key. So, we present a new method that can improve the efficiency when range-query is specified by a key attribute as well as other attributes. The presented method can guarantee the independence of separated modules and alleviate overheads for range-query using partial index.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.93-107
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• 2007

In this paper, an adaptive range aggregation spatial index method is proposed for spatial range query in ubiquitous sensor networks. As the ubiquitous sensor networks are the new information-oriented paradigm, many energy efficient spatial range query methods in ubiquitous sensor networks environment are studied vigorously. In sensor networks, users can monitor environment scalar data such as temperature and humidity during user defined time and spatial ranges. In order to execute spatial range query efficiently, rectangle based index methods are proposed, such as SPIX. But they define the return path as the opposite of its query transmit path. However, the sensor nodes in queried ranges are closed to each other, they can't aggregate the sensed value in a queried range because their query transmission paths are different. As a result, the previous methods waste energy unnecessarily to aggregate sensing data out of the queried range. In this paper, an adaptive aggregation index method is proposed that can aggregate values in a user defined range adaptively by using its neighbor information. It is shown that sensor power is saved efficiently by using the proposed method over the performance evaluation.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.85-92
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• 2005

Recently, query processing techniques for the multi-dimensional data like images have been widely used to perform content-based retrieval of the data . Range query and Nearest neighbor query are widely used multi dimensional queries . This paper Proposes the efficient pruning strategies for k-nearest neighbor query in R-tree variants indexing structures. Pruning strategy is important for the multi-dimensional indexing query processing so that search space can be reduced. We analyzed the Pruning strategies and perform experiments to show overhead and the profit of the strategies. Finally, we propose best use of the strategies.

• 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.

• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.507-516
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• 2009

In stream data processing system, generally the interval queries are in advance registered in the system. When a data is input to the system continuously, for realtime processing, a query indexing method is used to quickly search queries. Thus, a main memory-based query index with a small storage cost and a fast search time is needed for searching queries. In this paper, we propose a LVC-based(Limited Virtual Construct-based) query index method using a hashing to meet the both needs. In LVC-based query index, we divide the range of a stream into limited virtual construct, or LVC. We map each interval query to its corresponding LVC and the query ID is stored on each LVC. We have compared with the CEI-based query indexing method through the simulation experiment. When the range of values of input stream is broad and there are many short interval queries, the LVC-based indexing method have shown the performance enhancement for the storage cost and search time.