• Title, Summary, Keyword: Database Query Optimization

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The Design of the Selection and Alignment Queries Using Mobile Program (J2ME) for Database Query Optimization

  • Min, Cheon-Hong;Kumar, Prasanna
    • 한국경영정보학회:학술대회논문집
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    • pp.620-627
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    • 2008
  • In this paper, recognizing the importance of the database query optimization design methods, we implemented mobile database with mobile program (J2ME) which is a useful database procedures. In doing so, we emphasize the logical query optimization which brings mobile database to performance improvement. The research implies that the suggested mobile program (J2ME) would contribute to the realization of the efficient mobile database as the related technology develops in the future.

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The Design of the Selection and Alignment Queries Using Mobile Program (J2ME) for Database Query Optimization

  • Ko, Wan-Suk;Min, Cheon-Hong
    • 한국디지털정책학회:학술대회논문집
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    • pp.263-273
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    • 2003
  • Recognizing the importance of the database query optimization design methods, we implemented mobile database with mobile program (J2ME) which is a useful database procedures. In doing so, we emphasize the logical query optimization which brings mobile database to performance improvement. The research implies that the suggested mobile program (J2ME) would contribute to the realization of the efficient mobile database as the related technology develops in the future.

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A FRAMEWORK FOR QUERY PROCESSING OVER HETEROGENEOUS LARGE SCALE SENSOR NETWORKS

  • Lee, Chung-Ho;Kim, Min-Soo;Lee, Yong-Joon
    • Proceedings of the KSRS Conference
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    • pp.101-104
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    • 2007
  • Efficient Query processing and optimization are critical for reducing network traffic and decreasing latency of query when accessing and manipulating sensor data of large-scale sensor networks. Currently it has been studied in sensor database projects. These works have mainly focused on in-network query processing for sensor networks and assumes homogeneous sensor networks, where each sensor network has same hardware and software configuration. In this paper, we present a framework for efficient query processing over heterogeneous sensor networks. Our proposed framework introduces query processing paradigm considering two heterogeneous characteristics of sensor networks: (1) data dissemination approach such as push, pull, and hybrid; (2) query processing capability of sensor networks if they may support in-network aggregation, spatial, periodic and conditional operators. Additionally, we propose multi-query optimization strategies supporting cross-translation between data acquisition query and data stream query to minimize total cost of multiple queries. It has been implemented in WSN middleware, COSMOS, developed by ETRI.

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Cache Management Method for Query Forwarding Optimization in the Grid Database (그리드 데이터베이스에서 질의 전달 최적화를 위한 캐쉬 관리 기법)

  • Shin, Soong-Sun;Jang, Yong-Il;Lee, Soon-Jo;Bae, Hae-Young
    • Journal of Korea Multimedia Society
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    • v.10 no.1
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    • pp.13-25
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    • 2007
  • A cache is used for optimization of query forwarding in the Grid database. To decrease network transmission cost, frequently used data is cached from meta database. Existing cache management method has a unbalanced resource problem, because it doesn't manage replicated data in each node. Also, it increases network cost by cache misses. In the case of data modification, if cache is not updated, queries can be transferred to wrong nodes and it can be occurred others nodes which have same cache. Therefore, it is necessary to solve the problems of existing method that are using unbalanced resource of replica and increasing network cost by cache misses. In this paper, cache management method for query forwarding optimization is proposed. The proposed method manages caches through cache manager. To optimize query forwarding, the cache manager makes caching data from lower loaded replicated node. The query processing cost and the network cost will decrease for the reducing of wrong query forwarding. The performance evaluation shows that proposed method performs better than the existing method.

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Cost Models of Energy-based Query Optimization for Flash-aware Embedded DBMS (플래시 기반 임베디드 DBMS의 전력기반 질의 최적화를 위한 비용 모델)

  • Kim, Do-Yun;Park, Sang-Won
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.3
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    • pp.75-85
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    • 2008
  • The DBMS are widely used in embedded systems. The flash memory is used as a storage device of a embedded system. The optimizer of existing database system assumes that the storage device is disk. There is overhead to overwrite on flash memory unlike disk. The block of flash memory should be erased before write. Due to this reason, query optimization model based on disk does not adequate for flash-aware database. Especially embedded system should minimize the consumption of energy, but consumes more energy because of excessive erase operations. This paper proposes new energy based cost model of embedded database and shows the comparison between disk based cost model and energy based cost model.

Bit-map Indexes and Their Selection Problem for Efficient Processing of Star Joins in Object Databases (객체 데이터베이스에서 스타 조인의 빠른처리를 위한 비트맵 색인 기법과 그의 선정 문제)

  • 조완섭;정태성;이현철;장혜경;안명상
    • Journal of Information Technology Applications and Management
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    • v.10 no.2
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    • pp.19-31
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    • 2003
  • We propose an indexing technique and an index selection algorithm for optimal OLAP query processing in object database systems, Although there are many research results on the relational database systems for OLAP Query processing, few researches have been done on the object database systems. Since OLAP queries represent complex business logic on a huge data ware-house, object database systems supporting the OLAP queries should have higher performance. Proposed bitmap index structure is an extension of conventional bitmap indexes for adapting object databases and provides higher performance with lower space overhead. We also propose a linear time solution of the index selection problem that will be used in the OLAP query optimization process.

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Cost-based Optimization of Extended Boolean Queries (확장 불리언 질의에 대한 비용 기반 최적화)

  • 박병권
    • Journal of the Korean Society for information Management
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    • v.18 no.3
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    • pp.29-40
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    • 2001
  • In this paper, we suggest a query optimization algorithm to select the optimal processing method of an extended boolean query on inverted files. There can be a lot of methods for processing an extended boolean query according to the processing sequence oh the keywords con tamed in the query, In this sense, the problem of optimizing an extended boolean query it essentially that of optimizing the keyword sequence in the query. In this paper, we show that the problem is basically analogous to the problem of finding the optimal join order in database query optimization, and apply the ideas in the area to the problem solving. We establish the cost model for processing an extended boolean query and develop an algorithm to filled the optimal keyword-processing sequence based on the concept of keyword rank using the keyword selectivity and the access costs of inverted file. We prove that the method selected by the optimization algorithm is really optimum, and show, through experiments, that the optimal method is superior to the others in performance We believe that the suggested optimization algorithm will contribute to the significant enhancement of the information retrieval performance.

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Distributed Database Design using Evolutionary Algorithms

  • Tosun, Umut
    • Journal of Communications and Networks
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    • v.16 no.4
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    • pp.430-435
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    • 2014
  • The performance of a distributed database system depends particularly on the site-allocation of the fragments. Queries access different fragments among the sites, and an originating site exists for each query. A data allocation algorithm should distribute the fragments to minimize the transfer and settlement costs of executing the query plans. The primary cost for a data allocation algorithm is the cost of the data transmission across the network. The data allocation problem in a distributed database is NP-complete, and scalable evolutionary algorithms were developed to minimize the execution costs of the query plans. In this paper, quadratic assignment problem heuristics were designed and implemented for the data allocation problem. The proposed algorithms find near-optimal solutions for the data allocation problem. In addition to the fast ant colony, robust tabu search, and genetic algorithm solutions to this problem, we propose a fast and scalable hybrid genetic multi-start tabu search algorithm that outperforms the other well-known heuristics in terms of execution time and solution quality.