Auto-selection and management of dynamic SGA parameters in RDBMS

In the 21^st century, automation is the biggest need and a challenge also for all kind of systems. As we know in the present world machines are more capable to analyze large amount of data and able to take quick decisions based on the analysis compare to human. So in the field of performance tuning of a system, it is also required to eliminate the human intervention and introduce the analysis and decision power of the machine. From the past experience we know that the human intervention is costly and error prone for management of a system. The same experience has been used by us to automate the process of performance tuning in database management system. Most of the systems are still depends on the capability of DBA and require his/her intervention for performance monitoring and diagnosing process. The work carried out by us is a set of algorithms and a tool based on these algorithms to eliminate the dependency of DBA for performance tuning.