Graduation Year


Document Type




Degree Granting Department

Computer Science

Major Professor

Yicheng Tu, Ph.D.

Committee Member

Miguel Labrador, Ph.D.

Committee Member

Gang Ding, Ph.D.


Workload Management, Memory Contention, Control Theory, Experimental Platform, Optimal Multiple Query Processing


Databases are very complex systems that require database system administrators to perform system tuning in order to achieve optimal performance. Memory tuning is vital to the performance of a database system because when the database workload exceeds its memory capacity, the results of the queries running on a system are delayed and can cause substantial user dissatisfaction. In order to solve this problem, this thesis presents a platform modeled after a closed control feedback loop to control the level of multi-query processing. Utilizing this platform provides two key assets. First, the system identification is acquired, which is one of two crucial steps involved in developing a closed feedback loop. Second, the platform provides a means to experimentally study database tuning problem and verify the effectiveness of research ideas related to database performance.