Abstract

1. Power-Aware DBMS: Potential and ChallengesYi-cheng Tu *, Xiaorui Wang §, and Zichen Xu * and Peyman Behzadnia **Department of Computer Science & Engineering, University of South Florida § Department of Electrical Engineering & Computer Science, University of Tennessee Abstract Energy consumption has become a first-class optimization goal in computing system design and implementation. Database systems, being a major consumer of computing resources (thus energy) in modern data centers, also face the challenges of going green. In this position paper, we describe our vision on this new direction of database system research, and report the results of our recent work on this topic. We describe our ideas on the key issues in designing a power-aware DBMS (P-DBMS) and sketch our solutions to such issues. Specifically, we believe that the ability for the DBMS to dynamically adjust various knobs to satisfy energy (and performance) goals is the main technical challenge in this paradigm. To address that challenge, we propose dynamic modeling and tuning techniques based on formal feedback control theory. Our preliminary data clearly show that the energy savings can be significant. Feedback Control for Power Optimization • In our P-DBMS design, the power savings are achieved by adapting the following two mechanisms: • Power-aware Query Optimization • Feedback Control for Power Optimization The basic idea is to start from a difference equation with unknown parameters and orders in the following general form: (3) where R(k) is the output (i.e., throughput in our problem) at the end of control period k; n(k) is the input at period k, x and y are the orders of the system output and input, respectively; aiand biare plant-specific parameters. Power-aware Query Optimization • Power Model (1) c′ is a vector holding the marginal power cost of the basic operations in the plan, and oT is named the power profile of database operations. • Plan Cost Model (2) The superiority (i.e., final cost) of a plan should be a function of the plan’s power cost E and performance T, and the structure and parameter of the function should reflect the DBA’s preference on the tradeoffs to take between the two dimensions. This idea is illustrated in Fig. 2. Empirical Result OVERVIEW OF P-DBMS DESIGN Problem. Given a performance bound, the power consumption of the database system should be minimized? Figure 3. CPU and hard disk’s peak power responded to online changes of n. Note that this model includes a coefficient n that can be configured to reflect the relative importance of P and T. Intuitively, this model implies that the query optimizer is willing to sacrifice a dn-time degradation in performance to achieve a d-time power reduction. • Summary • Building such a PDBMS system • How such issues can be resolved. • P-DBMS is an approach for tackling the problem of energy-efficient database systems. Contacts: zxu5@cse.usf.edu, ytu@cse.usf.edu, xwang@ece.utk.edu Figure 2. Pareto curves formed by different cost functions Figure 1. The Infrastructure of P-DBMS