NDLI: Adaptive Self-Tuning Techniques for Performance Tuning of Database Systems: A Fuzzy-Based Approach

Content Provider	IEEE Xplore Digital Library
Author	Rodd, S.F. Kulkarni, U.P.
Copyright Year	2013
Description	Author affiliation: Comput. Sci. Eng., Graphic Era Univ., Dehradun, India (Rodd, S.F.) \|\| Comput. Sci. & Eng., SDMCET, Dharwar, India (Kulkarni, U.P.)
Abstract	Self-tuning of Database Management Systems(DBMS) offers important advantages such as improved performance, reduced Total Cost of Ownership(TCO), eliminating the need for an exert Database Administrator(DBA) and improved business prospects. Several techniques have been proposed by researchers and the database vendors to self-tune the DBMS. However, the research focus was confined to physical tuning techniques and the algorithms used in existing methods for self-tuning of memory need analysis of large statistical data. As result, these approaches are not only computationally expensive but also do not adapt well to highly unpredictable workload types and user-load patterns. Hence, in this paper a fuzzy based self-tuning approach has been proposed wherein, three inputs namely, Buffer-Hit-Ratio, Number of Users and Database size are extracted from the Database management system as sensor inputs that indicate degradation in performance and key tuning parameters called the effectors are altered according to the fuzzy-rules. The fuzzy rules are framed after a detailed study of impact of each tuning parameter on the response-time of user queries. The proposed self-tuning architecture is based on Monitor, Analyze, Plan and Execute(MAPE) feedback control loop framework [1] and has been tested under various workload types. The results have been validated by comparing the performance of the proposed self-tuning system with the auto-tuning feature of commercial database systems. The results show significant improvement in performance under various workload-types, user-load variations.
Starting Page	124
Ending Page	129
File Size	218856
Page Count	6
File Format	PDF
ISBN	9780769551272
DOI	10.1109/ADCONS.2013.49
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-15
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	User-load Satellite broadcasting Fuzzy Inference System Database Administrator Tuning-moderation Tuning Fuzzy logic Computer science Buffer-Hit-Ratio Self-tuning Workload-types System performance Database systems
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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