• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.67-76
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• 2018

This paper addresses the problem of efficient processing of region monitoring queries. The centralized methods used for existing region monitoring query processing assumes that the mobile object periodically sends location-updates to the server and the server continues to update the query results. However, a large amount of location updates seriously degrade the system performance. Recently, some distributed methods have been proposed for region monitoring query processing. In the distributed methods, the server allocates to all objects i) a resident domain that is a subspace of the workspace, and ii) a number of nearby query regions. All moving objects send location updates to the server only when they leave the resident domain or cross the boundary of the query region. In order to allocate the resident domain to the moving object along with the nearby query region, we use a query index structure that is constructed by splitting the workspace recursively into equal halves. However, However, the above index structure causes unnecessary division, resulting in deterioration of system performance. In this paper, we propose an adaptive split method to reduce unnecessary splitting. The workspace splitting is dynamically allocated i) considering the spatial relationship between the query region and the resultant subspace, and ii) the distribution of the query region. We proposed an enhanced QR-tree with a new splitting method. Through a set of simulations, we verify the efficiency of the proposed split methods.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.23-30
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• 2004

In order to approximate the spatial query result size we partition the input rectangles into subsets and estimate the query result size based on the partitioned spatial area. In this paper we examine query result size estimation in skewed data. We examine the existing spatial partitioning techniques such as equi-area and equi-count partitioning, which are analogous to the equi-width and equi-height histograms used in relational databases, and examine the other partitioning techniques based on spatial indexing. In this paper we propose a new spatial partitioning technique based on the Hilbert space filling curve. We present a detailed experimental evaluation comparing the proposed technique and the existing techniques using synthetic as well as real-life datasets. The experiments showed that the proposed partitioning technique based on the Hilbert space filling curve achieves better query result size estimation than the existing techniques for space query size, bucket numbers, skewed data, and spatial data size.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.867-878
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• 2006

In the past few years, the research of sensor networks is forced dramatically. Specially, while the research for maintaining the power of a sensor is focused, we are also concerned nth query processing related with the optimization of multiple continuous queries for decreasing in unnecessary energy consumption of sensor networks. We present the fragmentation algorithm to solve the redundancy problem in multiple continuous queries that increases in the count or the amount of transmitting data in sensor networks. The fragmentation algorithm splits one query into more than two queries using the query index (QR-4ree) in order to reduce the redundant query region between a newly created query and the existing queries. The R*-tree should be reorganized to the QR-tree right to the structure suggested. In the result, we preserve 20 percentage of the total energy in the sensor networks.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.23-32
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• 2004

The query optimizer's important task while a query is invoked is to estimate the fraction of records in the databases that satisfy the given query condition. The query result size estimation in spatial databases, like relational databases, proceeds to partition the whole input into a small number of subsets called “buckets” and then estimate the fraction of the input in the buckets. The accuracy of estimation is determined by the difference between the real data counts and approximations in the buckets, and is dependent on how to partition the buckets. Existing techniques for spatial databases are equi-area and equi-count techniques, which are respectively analogous in relation databases to equi-height histogram that divides the input value range into buckets of equal size and equi-depth histogram that is equal to the number of records within each bucket. In this paper we propose a new partitioning technique that determines buckets according to the maximal difference of area which is defined as the product of data ranges End frequencies of input. In this new technique we consider both data values and frequencies of input data simultaneously, and thus achieve substantial improvements in accuracy over existing approaches. We present a detailed experimental study of the accuracy of query result size estimation comparing the proposed technique and the existing techniques using synthetic as well as real-life datasets. Experiments confirm that our proposed techniques offer better accuracy in query result size estimation than the existing techniques for space query size, bucket number, data number and data size.

• The KIPS Transactions:PartD
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• v.10D no.4
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• pp.621-638
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• 2003

As demand of XML documents in the Web increases, Web service applications that manage XML documents as their resource are increasing. The view mechanism for XML data could be considered for effective in query processing in these Web service applications. If the XML query results are maintained as XML materialized views and their relevant XML query is processed using them, the query response time could be reduced. There are two types of processing an in path expression, which is one of the core features of XML query languages, using XML materialized views. One is the type where the complete query result is obtained from the materialized view, and the other is the type where some of the result is obtained from the materialized view and the rest is from the underlying XML documents. In this paper, we investigate the second type. An XML query in this paper is an XML path expression which is one of the core features of XML query languages. We first describe the storage structures of the XML materialized views derived from the underlying XML documents in the XML repository. Then, we propose the algorithms to decompose a given XML query into the subquery against the materialized view and the subquery against the underlying XML documents, and to integrate the results of these subqueries. Through performance evaluation, we figure out the condition under which our XML query decomposition using materialized views is more effective than the conventional processing.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.27-42
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• 2009

In realizing ubiquitous computing, techniques of efficiently using the limited resource at client such as mobile devices are required. With a mobile device with limited amount of memory, the techniques of XML stream query processing should be employed to process queries over a large volume of XML data. Recently, several techniques were proposed which fragment XML documents into XML fragments and stream them for query processing at client. During query processing, there could be great difference in resource usage (query processing time and memory usage) depending on how the source XML documents are fragmented. As such, an efficient fragmentation technique is needed. In this paper, we propose an XML fragmentation technique whereby resource efficiency in query processing at client could be enhanced. For this, we first present a cost model of query processing over XML fragment stream. Then, we propose an algorithm for resource-efficient XML fragmentation. Through implementation and experiments, we showed that our fragmentation technique outperformed previous techniques both in processing time and memory usage. The contribution of this paper is to have made the techniques of query processing over XML fragment stream more feasible for practical use.

• Journal of KIISE:Databases
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• v.34 no.2
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• pp.166-178
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• 2007

The ALE specification of EPCglobal is leading the development of RFID standards, includes the Event Cycle Specification (ECSpec) describing how long a cycle is, how to filter RFID tag data and which reader is interested in. The ECSpec is a specification for filtering and collecting RFID tag data. It is registered to a middleware for long time and is evaluated to return results satisfying the requirements included in it. Thus, it is quite similar to the continuous query. It can be transformed into a continuous query as its predicate in WHERE clause is characterized by the long interval. Long intervals cause problems deteriorating insertion and search performance of existing query indices. In this paper, we propose a TLC-index as a new query index structure for long interval data. The TLC-index has hybrid structure that uses the cell construct of CQI-index with the virtual construct of VCR-index for partitioning long intervals. The TLC-index can reduce the storage cost and improve the insertion performance through decomposing long intervals into one or more cell constructs that have long size. It can also improve the search performance through decomposing short intervals into one or more virtual constructs that have short size enough to fit into those intervals.

• Journal of KIISE:Databases
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• v.32 no.2
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• pp.177-192
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• 2005

In this paper, we introduce a structural redundancy method. It reduces the query processing cost incurred when reconfiguring an XML document from divided XML data in shredding XML documents into relations. The fundamental idea is that query performance can be enhanced by analyzing query patterns and replicating data essential for the query performance. For the practical and effective structural redundancy, we analyzed three types of ID, VALUE, and SUBTREE replication. In addition, if given XML data and queries are very large and complex, it can be very difficult to search optimal redundancy set. Therefore, a heuristic search method is introduced in this paper. Finally, XML query processing cost arising by employing the structural redundancy, and the efficiency of proposed search method arc analyzed experimentally It is manifest that XML read query is performed more quick]y but XML update query is performed more slowly due to the additional update consistency cost for replicas. However, experimental results showed that in-place ID replication is useful even in having excessive update cost. It was also observed that multiple-place SUBTREE replication can enhance read query performance remarkably if only update cost is not excessive.

• The Journal of Korean Association of Computer Education
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• v.18 no.5
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• pp.63-70
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• 2015

In the environment that the complex conditions need to be satisfied, skyline query have been applied to various field. To processing a skyline query in centralized scheme, several techniques have been suggested and recently map/reduce platform based approaches has been proposed which divides data space into multiple partitions for the vast volume of multidimensional data. However, the performances of these approaches are fluctuated due to the uneven data loading between servers and redundant tasks. Motivated by these issues, this paper suggests a novel technique called MR-DEAP which solves the uneven data loading using the random sampling. The experimental result gains the proposed MR-DEAP outperforms MR-Angular and MR-BNL scheme.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.1-8
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• 2003

Various methods have been studying to maintain and apply the multimedia inform abruptly increasing over all social fields, in recent years. For retrieval of still images, we is implemented content-based image retrieval system in this paper that make possible to retrieve similar objects from image database after segmenting query object from background if user request query. Query image is processed median filtering to remove noise first and then object edge is detected it by canny edge detection. And query object is segmented from background by using convex hull. Similarity value can be obtained by means of histogram intersection with database image after securing color histogram from segmented image. Also segmented image is processed gray convert and wavelet transform to extract spacial gray distribution and texture feature. After that, Similarity value can be obtained by means of banded autocorrelogram and energy. Final similar image can be retrieved by adding upper similarity values that it make possible to not only robust in background but also better correct object retrieval by using object segmentation method.