Earticle

초록

영어

Database administrators are demanded to acquire much knowledges and take great efforts for keeping consistent performance in system. Various principles, methods, and tools have been proposed in many studies and commercial products in order to alleviate such burdens on database administrators, and it has resulted to the automation of DBMS which reduces the intervention of database administrator. This paper suggests a resource selection method that estimates the status of the database system based on the workload characteristics and that recommends tuneable resources. Our method tries to simplify selection information on DBMS status using data-mining techniques, enhance the accuracy of the selection model, and recommend tuneable resource. For evaluating the performance of our method, instances are collected in TPC-C and TPC-W workloads, and accuracy are calculated using 10 cross validation method. comparisons are made between our scheme and the method which uses only the classification procedure without any simplification of informations. It is shown that our method has over 90% accuracy and can perform tuneable resource selection.

목차

Abstract
 1. 서론
 2. 튜닝가능한 자원 선택 방법
 3. 튜닝가능한 자원 선택을 위한 실험환경
 4. 튜닝가능한 자원선택 방법의 수행 결과
 5. 결론 및 향후 계획
 참고문헌

키워드

저자

• 김혜숙 [ Hyesook Kim | 숭실대학교 전산원 멀티미디어학과 교수 ]
• 오정석 [ Jeong Soek Oh | 한국가스안전공사 가스안전연구원 선임연구원 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  JITAM [Journal of Information Technology Applications and Management]

• 간기

  격월간

• pISSN

  1598-6284

• eISSN

  2508-1209

• 수록기간

  1999~2026

• 십진분류

  KDC 005 DDC 005