Monitoring, Modelling and Identification of Data Center Servers

Abstract: Energy efficient control of server rooms in modern data centers can help reducing the energy usage of this fast growing industry. Efficient control, however, cannot be achieved without: i) continuously monitoring in real-time the behaviour of the basic thermal nodes within these infras- tructures, i.e., the servers; ii) analyzing the acquired data to model the thermal dynamics within the data center. Accurate data and accurate models are indeed instrumental for implementing efficient data centers cooling strategies. In this thesis we focus on Open Compute Servers, a class of servers designed in an open-source fashion and used by big players like Facebook. We thus propose a set of appropriate methods for collecting real-time data from these platforms and a dedicated thermal model describing the thermal dynamics of the CPUs and RAMs of these servers as a function of both controllable and non-controllable inputs (e.g., the CPU utilization levels and the air mass flow of the server’s fans). We also identify this model from real data and provide the results so to be reusable by other researchers.