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Towards Self-Tuning of Dynamic Resources for Workloads
Adelaide, Australia January 23-January 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WKDD.2008.112First International Workshop on Knowl ...
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Fu Duan, Yongjie Han, Qiuyong Zhao, Keming Xie, "Towards Self-Tuning of Dynamic Resources for Workloads," International Workshop on Knowledge Discovery and Data Mining, pp. 297-300, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008.
 
 
BibTex
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@article{ 10.1109/WKDD.2008.112,
author = {Fu Duan and Yongjie Han and Qiuyong Zhao and Keming Xie},
title = {Towards Self-Tuning of Dynamic Resources for Workloads},
journal ={International Workshop on Knowledge Discovery and Data Mining},
volume = {0},
year = {2008},
isbn = {0-7695-3090-7},
pages = {297-300},
doi = {http://doi.ieeecomputersociety.org/10.1109/WKDD.2008.112},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - International Workshop on Knowledge Discovery and Data Mining
TI - Towards Self-Tuning of Dynamic Resources for Workloads
SN - 0-7695-3090-7
SP297
EP300
A1 - Fu Duan,
A1 - Yongjie Han,
A1 - Qiuyong Zhao,
A1 - Keming Xie,
PY - 2008
VL - 0
JA - International Workshop on Knowledge Discovery and Data Mining
ER -
 
In self-tuning of database performance research area, the optimization of dynamic resources is important. This paper focused on the self-tuning of dynamic resources on the base of feedback mechanism, designed and achieved a simple model combined with Oracle database. This model gave an evaluating principle of system performance, and could adjust system parameters automatically to achieve the goal of system performance. And an evaluation model was designed to evaluate the performance state of the running system. The result after the self-tuning of some parameters was illustrated by simulating various workloads.
Citation:
Fu Duan, Yongjie Han, Qiuyong Zhao, Keming Xie, "Towards Self-Tuning of Dynamic Resources for Workloads," wkdd, pp.297-300, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008
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