Measuring and Analyzing Energy Consumption of the Data Center

Abstract

Data centers are continuously expanding, so does the energy consumed to power their infrastructure. Server is the major component of data center’s computer rooms, which runs the most intensive computational workloads and stores the data. Server is responsible for more than a quarter of the total energy consumption of data center. This thesis is focused on analyzing and predicting the energy consumption of the server. Three major components are considered in our study; the processor, the access memory and the network interface controller. We collect data from these components and analyze them using linear regression Lasso model with non-negative coefficients. A power model is proposed for predicting energy consumption at the system-level. The model takes as input CPU cycles and data Translation Lookaside Buffer loads, and predicts the energy consumption of the server with 5.33% median error regardless of its workload