Valdivia-Garcia, Harold D.
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Publication Empirical cost models for estimating power and energy consumption in database servers(2010) Valdivia-Garcia, Harold D.; Rodríguez-Martínez, Manuel; College of Engineering; Santiago-Santiago, Nayda G.; Rivera-Vega, Pedro I.; Department of Electrical and Computer Engineering; Walker-Ramos, Uroyoán R.The explosive growth in the size of data centers, coupled with the wide- spread use of virtualization technology has brought power and energy consumption as major concerns for data center administrators. Provisioning decisions must take into consideration not only target application performance but also the power demands and total energy consumption incurred by the hardware and software to be deployed at the data center. Failure to do so will result in damaged equipment, power outages, and inefficient operation. Since database servers comprise one of the most popular and important server applications de- ployed in such facilities, it becomes necessary to have accurate cost models that can predict the power and energy demands that each database workloads will impose in the system. In this work we present an empirical methodology to esti- mate the power and energy cost of database operations. Our methodology uses multiple-linear regression to derive accurate cost models that depend only on readily available statistics such as selectivity factors, tuple size, numbers columns and relational cardinality. Moreover, our method does not need measurement of individual hardware components, but rather total power and energy consumption measured at a server. We have implemented our methodology, and ran experiments with several server configurations. Our experiments indicate that we can predict power and energy more accurately than alternative methods found in the literature.