Database Systems Journal · 2012 · 20 citations · 3 references
Open access
ComputingComputer ScienceInformation SystemsAutomationDatabasesOperating SystemsDatabase AdministrationDatabase ManagementPerformance TuningAuto-tuningDatabase AutomationDatabase Management SystemsOperating System ArchitectureParameter TuningSystem TuningTuning
In present scenario the manual work (Done by Human) cost more to an organization than the automatic work ( Done by Machine)and the ratio is increasing day by day as per the tremendous increment in Machine (Hardware + Software) Intelligence. We are moving towards the world where the Machines will be able to perform better than today by their own intelligence. They will adjust themselves as per the customer’s performance need. But to make this dream true, lots of human efforts (Theoretical and Practical) are needed to increase the capability of Machines to take their own decision and make the future free from manual work and reduce the working cost. Our life is covered with the different types of systems working around. The information system is one of them. All businesses are having the base by this system. So there is the most preference job of the IT researcher to make the Information system self-Manageable. The Development of well-established frameworks are needed to made them Auto-tuned is the basic need of the current business.The DBMS vendors are also providing the Auto-Tune packages with their DBMS Application. But they charge for these Auto-Tune packages. This extra cost of packages can be eliminated by using some basic Operating system utilities (e.g. VB Script, Task Scheduler, Batch Files, and Graphical Utility etc.). We have designed a working framework for Automatic Tuning of DBMS by using the Basic Utilities of Operating System (e.g. Windows) .These utilities will collect the statistics of SGA dynamic Parameters. The Framework will automatically analyze these SGA Parameter statistics and give suggestions fordiagnose the problem. In this paper we have presented that framework with practical Implementation.
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Towards Automated Performance Tuning for Complex Workloads
Kurt P. Brown, Manish Mehta, Michael J. Carey et al. · Minds at UW (University of Wisconsin) · 1994 · 93 citations · Full text
Towards Self-Tuning Memory Management for Data Servers
Gerhard Weikum, Arnd Christian König, Achim Kraiß et al. · 1999 · 28 citations