Digital Control of Dynamic Systems
Digital Control of Dynamic Systems
Proceedings of the VLDB Endowment
The Claremont report on database research
ACM SIGMOD Record
Temperature-constrained power control for chip multiprocessors with online model estimation
Proceedings of the 36th annual international symposium on Computer architecture
Performance Evaluation and Benchmarking: First TPC Technology Conference, TPCTC 2009, Lyon, France, August 24-28, 2009, Revised Selected Papers
Analyzing the energy efficiency of a database server
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
A survey on energy-efficient data management
ACM SIGMOD Record
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In today's large-scale data centers, energy costs (i.e., the electricity bill) are projected to outgrow that of hardware. Despite a long history of research in energy-saving techniques, especially low-power hardware, little work has been done to improve the power efficiency of data management software. Power-aware computing research at the application level has been found to be synergistic to that at the hardware and OS levels because it can provide more opportunities for energy reduction in the underlying systems. This paper describes the author's thesis work on creating a power-aware database management (P-DBMS) and initial ideas on the design of such systems, with the focus on a power-aware query optimization module inside the DBMS. We discuss the main technical challenges in designing the optimizer and present our strategies to meet such challenges. We focus our discussions on a power model to accurately measure the energy costs of query executions plans, and a cost evaluation model for plan selection. An important feature of this work is the formal control-theoretic methods we use to model and optimize the database towards the performance and energy saving goals. This rigorous design methodology is in sharp contrast to heuristic-based adaptive solutions that rely on extensive empirical evaluation and manual tuning. Our experiments using a power-aware query optimizer under our initial design show that there exist significant potential in power/energy savings.