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Reseach Article

Fuzzy Controlled Architecture for Performance Tuning of Database Management System

by S. F. Rodd, Umakant P. Kulkarni, A. R. Yardi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 39 - Number 5
Year of Publication: 2012
Authors: S. F. Rodd, Umakant P. Kulkarni, A. R. Yardi
10.5120/4813-7050

S. F. Rodd, Umakant P. Kulkarni, A. R. Yardi . Fuzzy Controlled Architecture for Performance Tuning of Database Management System. International Journal of Computer Applications. 39, 5 ( February 2012), 1-5. DOI=10.5120/4813-7050

@article{ 10.5120/4813-7050,
author = { S. F. Rodd, Umakant P. Kulkarni, A. R. Yardi },
title = { Fuzzy Controlled Architecture for Performance Tuning of Database Management System },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 39 },
number = { 5 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume39/number5/4813-7050/ },
doi = { 10.5120/4813-7050 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:25:37.472995+05:30
%A S. F. Rodd
%A Umakant P. Kulkarni
%A A. R. Yardi
%T Fuzzy Controlled Architecture for Performance Tuning of Database Management System
%J International Journal of Computer Applications
%@ 0975-8887
%V 39
%N 5
%P 1-5
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Database Management Systems deliver higher performance only when they are properly tuned. Database tuning is complicated due to the fact that several conflicting tuning parameters have to be adjusted simultaneously for a variety of workload types and the highly unpredictable traffic patterns. The Database Administrator(DBA) has to be an expert and using his experience and expertise must judiciously decide the extent of tuning of the most important tuning factors so as to ensure the required level of performance in terms of response time and throughput. The process of tuning being complex and to keep the cost of ownership low, it is desirable to build self tuning database systems. In this paper, a new tuning architecture based on fuzzy logic is presented, where in, the control action is expressed in linguistic terms. In this system the key performance indicators are fuzzified, appropriate fuzzy rules are employed to estimate the extent of tuning required for a few important tuning parameters. After defuzzification, a control action is initiated to scale up the system performance. The experimental results obtained for different workload types and the user load, indicate that it is possible to significantly improve the query response time using this technique.

References
  1. S. Agarwal and et.al., “Automated Selection of Materialized Views and Indexes”, Conference Proceedings, VLDB, 2007.
  2. Surjit Choudhuri, Vivek Narasayya, “Self tuning database systems : A Decade progress”, Microsoft Research. 2007.
  3. Philip Koopman, “Elements of the Self-Healing System Problem Space”, IEEE Data Engineering Bulletin. 2004.
  4. Peng Liu, “Design and Implementation of Self healing Database system”, IEEE Conference, 2005.
  5. Yi-Cheng Tu, Gang Ding, “Control-Based Tuning under Dynamic Workloads, IEEE Conference 2007.
  6. Rimma V. Nehme, “Database, Heal Thyself”, Data Engineering Workshop April 2008.
  7. C.C.Lee, "Fuzzy Logic in Control Systems", IEEE Trans. on Systems, Man, and Cybernetics, SMC, Vol. 20, No. 2, 1990, pp. 404-35
  8. Debnath, B.K.; Lilja, D.J.; Mokbel, M.F., “SARD: A statistical approach for ranking database tuning parameters”, Data Engineering Workshop, 2008. ICDEW 2008. IEEE 24th International Conference, April 2008 .
  9. Wiese, David; Rabinovitch, Gennadi, “Knowledge Management in Autonomic Database Performance Tuning”, 20-25 April 2009.
  10. Ahmed A. Soror, Ashraf Aboulnaga, Kenneth Salem, “Database Virtualization : A new Frontier for Database Tuning and Physical Design”, IEEE 2007, pp 388-394.
  11. Stephan Krumpass, Andreas Scholz, Martina, “Quality of Serve Enabled Management of Database Workloads, Bulletin of IEEE Computer Society on Data Engineering, 2008.
  12. Choudhuri and G. Weikum, “Rethinking Database System Architecture: Towards a Self Tuning RISC style Database System”, in VLDB, 2000, pp 1-10.
  13. S. W. Cheng, D. Garlan et. al, “Architecture based Self Adaptation in the presence of multiple objectives”, Proceedings of 2006 International journal of Computer Systems and Engineering., 2006.
  14. Sanjay Agarwal, Nicolas Bruno, Surajit Chaudhari, “AutoAdmin: Self Tuning Database System Technology”, IEEE Data Engineering Bulletin, 2006.
  15. DageVille and K. Dias, “Oracle’s self tuning architecture and solutions”, IEEE Data Engg. Bulletin, Vol 29, 2006.
  16. Gerhar Weikum, Axel Moenkerngerg et. al., Self-tuning Database Technology and Information Services : From wishful thing to viable Engineering”, Parallel and Distributed Information System 1993.
  17. Chaudhuri, S.; Weikum G, “Foundations of Automated Database Tuning”, Data Engineering, April 2006.
  18. Satish, S.K.; Saraswatipura, M.K.; Shastry, S.C, “DB2 performance enhancements using Materialized Query Table for LUW Systems”, 2007. ICONS '07. Second International Conference, April 2007.
  19. Daniel Manasce, Bruno D., Daniel Barbara, “Fractal Characterization of Web Workloads”, 2002.
  20. J. Abanoyi, L. Nyagi, F. Seibefertz, ‘Adaptive Sugeno Fuzzy Control : A Case Study “, IEEE Conference 2002.
Index Terms

Computer Science
Information Sciences

Keywords

Buffer Hit Ratio Workload Fuzzy Rules Tuning Database Administrator