Graduation Year


Document Type




Degree Granting Department

Computer Science

Major Professor

Yicheng Tu, Ph.D.

Committee Member

Xiaorui Wang, Ph.D.

Committee Member

Ken Christensen, Ph.D.


Database Management System, Power Modeling, Power Estimation, Energy Concern, Query Optimization, Feedback Control


With the total energy consumption of computing systems increasing at a steep rate, much attention had been paid to the design of energy-efficient computing systems and applications. So far, database system design has focused on improving the performance of query processing. The objective of this study is to explore the potential of energy conservation in relational database management systems. The hypothesis is: by modifying the query optimizer in a Database management system (DBMS) to take the energy cost of query plans into consideration, we will be able to reduce the energy usage of database servers and control the tradeoffs between energy consumption and system performance. In this thesis, we provide an in-depth anatomy of typical queries in various benchmarks and qualitatively analyze the energy profile of such queries. The results of extensive experiments show that power savings in the range of 11% to 22% can be achieved by equipping the DBMS with a simple query optimizer that selects query plans based on both estimated processing time and energy requirements. We advocate more research efforts be invested into the design and evaluation of power-aware DBMSs in hope to reach higher level of energy efficiency.