• Journal of KIISE:Databases
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• v.34 no.4
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• pp.315-327
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• 2007

The performance of database applications with large sets of multidimensional data depends on the performance of its access methods and the underlying disk system. In modeling the disk system, even though modem disks are manufactured with multiple physical zones, conventional access methods have been developed based on a traditional disk model with many simplifying assumptions. Thus, there is a marked lack of investigation on how to enhance the performance of access methods given a zoned disk model. The paper proposes novel zoning techniques that can be applied to any multidimensional access methods, both static and dynamic, enhancing the effective data transfer rate of underlying disk system by fully utilizing its zone characteristics. Our zoning techniques include data placement algorithms for multidimensional index structures and accompanying localized query processing algorithms for range queries. The experimental results show that our zoning techniques significantly improve the query performance.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.409-422
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• 2006

In general, there can be many reusable intermediate results due to the overlapped windows and periodic execution intervals among Multiple Continuous Queries (MCQ) on data streams. In this regard, we propose an efficient greedy algorithm for a global query plan construction, called GAGPC. GAGPC first decides an execution cycle and finds the maximal Set(s) of Related execution Points (SRP). Next, GAGPC constructs a global execution plan to make MCQ share common join-fragments with the highest benefit in each SRP. The algorithm suggests that the best plan of the same continuous queries may be different according to not only the existence of common expressions, but the size of overlapped windows related to them. It also reflects to reuse not only the whole but partial intermediate results unlike previous work. Finally, we show experimental results for the validation of GAGPC.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.87-90
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• 2010

본 논문에서는 무선 방송 환경에서 XML에 대한 다양한 사용자 질의에 대하여 다중 채널을 통해 효과적으로 질의의 결과를 전송하기 위한 색인 기법을 고려한다. 이를 위해 서버측에서는 질의 결과뿐만 아니라 원본 XML상에서 질의 결과가 위치하는 계층 정보까지 파악이 가능한 비트 좌표 기반 색인 기법을 제안한다. 제안 기법의 시뮬레이션을 통해 다중 채널의 효과뿐만 아니라 색인으로 인해 빠른 응답시간을 가짐을 보인다.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1086-1090
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• 2010

In recent, as many applications of sensor networks increase, various techniques have been studied to efficiently operate network systems. The query optimization scheme that is one of such techniques has been studied to reduce the data transmission cost. The data transmission is of great importance to the energy consumption of sensor networks. In this paper, we propose an energy-efficient multiple queries processing scheme by sharing sensor readings for multiple queries, when they are occurred in sensor networks. The proposed scheme reduces unnecessary data transmissions among the sensor nodes by intuitively identifying their locations using the grid structure. It also efficiently shares the data by recognizing the redundant regions of sensor nodes. In order to show the superiority of the proposed scheme, we compare it with the existing scheme in various experiments. As the result, the proposed scheme reduces about 65% energy consumption over the existing scheme.

• The KIPS Transactions:PartD
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• v.12D no.5 s.101
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• pp.673-682
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• 2005

Distance browsing queries, namely k-nearest neighbor queries, are the most important queries in spatial database applications, e.g., Geographic Information Systems(GISs). Recently, GIS applications trends to extend themselves toward wide multi-user environments such as the Web. Since many techniques for such queries, where Hjaltason and Samet's algorithm is the most efficient one, were optimized for only one query, we need to complement them suitable for multi-user environments. It can be a good approach that we store many individual query results in a cache, i.e., query result caching and reuse them in evaluating incoming queries, j.e., query result matching. In this paper, we propose a complementary Hjaltason and Samet's algerian capable of reusing previous query results in a cache for answering distance browsing queries in multi-user GIS environments. Our experimental results conform the efficiency of our approach.

• Journal of KIISE:Databases
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• v.37 no.2
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• pp.121-126
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• 2010

This paper proposes an efficient index scheduling technique for kNN query processing in multiple wireless broadcast channel environment. Previous works have to wait for the next cycle if the required child nodes of the same parent node are allocated in the same time slot on multiple channel. Our proposed method computes the access frequencies of each node of R tree at the server before the generation of the R-tree index broadcast schedule. If they have high frequencies, we allocate them serially on the single channel. If they have low frequencies, we allocate them in parallel on the multiple channels. As a result, we can reduce the index node access conflicts and the long broadcast cycle. The performance evaluation shows that our scheme gives the better performance than the existing schemes.

• Journal of KIISE:Databases
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• v.29 no.4
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• pp.274-284
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• 2002

Queries on XML are based on paths in the data graph, which is represented as an edge labeled graph model. All proposed query languages for XML express queries using regular expressions to traverse arbitrary paths in the data graph. A meaningful query usually has several regular path expressions in it, but much of recent research is more concerned with optimizing a single path expression. In this paper, we present an efficient technique to process multiple path expressions in a query. We developed a data structure named as the path identifier(PID) to identify whether two given nodes lie on the fame path in the data graph or not, and utilized the PID for efficient processing of multiple path expressions. We implement our technique and present preliminary performance results.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.4
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• pp.31-37
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• 2003

This paper is a review of the large-scale information retrieval system, CONDOR. This system was developed by the consortium that consists of Chonbuk National University, Searchline Co. and Carnegie Mellon University. This system is based on the probabilistic model of information retrieval systems. The multi-language query processing, online document summarization based on query and dynamic hierarchy clustering of this system make difference of other systems. We test this system with 30 million web documents successfully.

• Journal of KIISE:Databases
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• v.35 no.1
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• pp.1-16
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• 2008

Join queries having heavy cost are necessary to Data Stream Management System in Sensor Network where plural short information is generated. It is reasonable that each join operator has a sliding-window constraint for preventing DISK I/O because the data stream represents the infinite size of data. In addition, the join operator should be able to take multiple inputs for overall results. It is possible for the MJoin operator with sliding-windows to do so. In this paper, we consider the data stream environment where multiple MJoin operators are registered and propose MMJoin which deals with issues of building and processing a globally shared query considering characteristics of the MJoin operator with sliding-windows. First, we propose a solution of building the global shared query execution plan. Second, we solved the problems of updating a window size and routing for a join result. Our study can be utilized as a fundamental research for an optimization technique for multiple continuous joins in the data stream environment.

• The KIPS Transactions:PartD
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• v.12D no.5 s.101
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• pp.689-698
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• 2005

Various systems are used to provide the location based services. But, the existing systems have some problems which have difficulties in dealing with faster services for above million people. In order to solve it, a multi-level DBMS which supports both fast data processing and large data management support should be used. The multi-level DBMS with snapshots has all the data existing in disk database and the data which are required to be processed for fast processing are managed in main memory database as snapshots. To optimize performance of this system for location based services, the query classification component which classifies the queries for efficient snapshot usage is needed. In this paper, the query classification component in multi-level DBMS for location based services is designed and implemented. The proposed component classifies queries into three types: (1) memory query, (2) disk query, (3) hybrid query, and increases the rate of snapshot usage. In addition, it applies division mechanisms which divide aspatial and spatial filter condition for partial snapshot usage. Hence, the proposed component enhances system performance by maximizing the usage of snapshot as a result of the efficient query classification.