• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.295-306
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• 2009

Query execution time minimization is an important objective in distributed database design. While total time minimization is an objective for On Line Transaction Processing (OLTP), response time minimization is for Decision Support queries. We formulate the sub-query allocation problem using analytical models and solve with genetic algorithm (GA). We show that query execution plans with total time minimization objective are inefficient from response time perspective and vice versa. The procedure is tested with simulation experiments for queries of up to 20 joins. Comparison with exhaustive enumeration indicates that GA produced optimal solutions in all cases in much less time.

• Journal of Digital Convergence
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• v.3 no.1
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• pp.149-163
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• 2005

Researches for NN(nearest neighbor) query which is often used in LBS system, have been worked. However. Conventional NN query processing techniques are usually meaningless in moving object management system for LBS since their results may be invalidated as soon as the query and data objects move. To solve these problems, in this paper we propose a new nearest neighbor query processing technique, called CTNN, which is possible to meet continuous trajectory nearest neighbor query processing. The proposed technique consists of Approximate CTNN technique which has quick response time, and Exact CTNN technique which makes it possible to search accurately nearest neighbor objects. Experimental results using GSTD datasets shows that the Exact CTNN technique has high accuracy, but has a little low performance for response time. They also shows that the Approximate CTNN technique has low accuracy comparing with the Exact CTNN, but has high response time.

• 한국디지털정책학회:학술대회논문집
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• 2005.06a
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• pp.517-530
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• 2005

Researches for NN(nearest neighbor) query which is often used in LBS system, have been worked. However, Conventional NN query processing techniques are usually meaningless in moving object management system for LBS since their results may be invalidated as soon as the query and data objects move. To solve these problems, in this paper we propose a new nearest neighbor query processing technique, called CTNN, which is possible to meet continuous trajectory nearest neighbor query processing. The proposed technique consists of Approximate CTNN technique which has quick response time, and Exact CTNN technique which makes it possible to search accurately nearest neighbor objects. Experimental results using GSTD datasets showed that the Exact CTNN technique has high accuracy, but has a little low performance for response time. They also showed that the Approximate CTNN technique has low accuracy comparing with the Exact CTNN, but has high response time.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.84-88
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• 2007

In a general tendency that DBMS is used as a tool for storing large size of triple knowledge, it still remains in issue that which DBMS schema should be designed for storing, managing, inferring, and querying the triple knowledge efficiently. In this paper, we present, in the view point of efficient query process, a method that processes a query using Expanded Class-Property Views (ECPV) and, as a result, improvement in response time. The response time of DBMS-based inference systems is proportioned to table size and the number of table join operations. The more query is complex, the more join operations it requires, and the longer response time it requires. ECPV is a table obtained by processing possible join operations before queries. To use ECPV in the query process, SPARQL queries should be converted into corresponding ECPV-based SQL queries. This paper describes the conversion process and shows the improvement in response time by experiments.

• Journal of Information Processing Systems
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• v.4 no.1
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• pp.9-16
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• 2008

This paper describes the design and implementation of a two-tier DBMS for handling massive data and providing faster response time. In the present day, the main requirements of DBMS are figured out using two aspects. The first is handling large amounts of data. And the second is providing fast response time. But in fact, Traditional DBMS cannot fulfill both the requirements. The disk-oriented DBMS can handle massive data but the response time is relatively slower than the memory-resident DBMS. On the other hand, the memory-resident DBMS can provide fast response time but they have original restrictions of database size. In this paper, to meet the requirements of handling large volumes of data and providing fast response time, a two-tier DBMS is proposed. The cold-data which does not require fast response times are managed by disk storage manager, and the hot-data which require fast response time among the large volumes of data are handled by memory storage manager as snapshots. As a result, the proposed system performs significantly better than disk-oriented DBMS with an added advantage to manage massive data at the same time.

• Journal of Communications and Networks
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• v.7 no.4
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• pp.417-428
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• 2005

The Voronoi diagram (VD) is the most suitable mechanism to find the nearest neighbor (NN) for mobile clients. In NN query processing, it is important to reduce the query response time, since a late query response may contain out-of-date information. In this paper, we study the issue of location dependent information services (LDISs) using a VD. To begin our study, we first introduce a broadcast-based spatial query processing methods designed to support NN query processing. In further sections, we introduce a generic method for location-dependent sequential prefetching and caching. The performance of this scheme is studied in different simulated environments. The core contribution of this research resides in our analytical proof and experimental results.

• Journal of KIISE:Databases
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• v.30 no.4
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• pp.408-419
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• 2003

Data warehouses are usually dedicated to the processing of quires issued by decision support system(DSS). The response time of DSS queries is typically several orders of magnitude higher than the one of OLTP queries. Since DSS queries are often submitted interactively, techniques for reducing their response time are important. The caching of query results is one such technique particularly well suited to the DSS environment. In this paper, we present a cache manager for such an environment. Specifically, we define a canonical form of query. The cache manager looks up a query based on the exact query match or using a suggested query split process if the query is found is non-canonical form or in canonical form, respectively. It dynamically maintains the cache content by employing a profit function which reflects in an integrated manner the query execution cost, the size of query result, the reference rate, the maintenance cost of each result due to updates of their base tables, and the frequency of such updates. We performed the experimental evaluation and it positively shows the performance benefit of our cache manager.

• 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.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.37-50
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• 2021

Query applications based on nested data, the most commonly used form of data representation on the web, especially precise query, is becoming more extensively used. MapReduce, a distributed architecture with parallel computing power, provides a good solution for big data processing. However, in practical application, query requests are usually concurrent, which causes bottlenecks in server processing. To solve this problem, this paper first combines a column storage structure and an inverted index to build index for nested data on MapReduce. On this basis, this paper puts forward an optimization strategy which combines query execution service tree and frequent sub-query trajectory to reduce the response time of frequent queries and further improve the efficiency of multi-user concurrent queries on large scale nested data. Experiments show that this method greatly improves the efficiency of nested data query.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9B
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• pp.1092-1097
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• 2011

An anti-collision protocol which tries to minimize the collision probability and identification time is the most important factor in all identification technologies. This paper focuses on methods to improve the efficiency of tag's process in identification systems. Our scheme, Binary Slotted Query Tree (BSQT) algorithm, is a memoryless protocol that identifies an object's ID more efficiently by removing the unnecessary prefixes of the traditional Query Tree (QT) algorithm. With enhanced QT algorithm, the reader will broadcast 1 bit and wait the response from the tags but the difference in this scheme is the reader will listen in 2 slots (slot 1 is for 0 bit Tags and slot 2 is for 1 bit Tags). Base on the responses the reader will decide next broadcasted bit. This will help for the reader to remove some unnecessary broadcasted bits which no tags will response. Numerical and simulation results show that the proposed scheme decreases the tag identification time by reducing the overall number of request.