Reducing Data Center Energy Consumption via Coordinated Cooling and Load Management


This paper presents a unified approach to data center energy management based on a modeling framework that characterizes the influence of key decision variables on computational performance, thermal generation, and power consumption. Temperature dynamics are modeled by a network of interconnected components reflecting the spatial distribution of servers, computer room air conditioning (CRAC) units, and non-computational components in the data center. A second network models the distribution of the computational load among the servers. Server power states influence both networks. Formulating the control problem as a Markov decision process (MDP), the coordinated cooling and load management strategy minimizes the integrated weighted sum of power consumption and computational performance. Simulation results for a small example illustrate the potential for a coordinated control strategy to achieve better energy management than traditional schemes that control the computational and cooling subsystems separately. These results suggest several directions for further research.

Workshop on Power Aware Computing and Systems, San Diego (CA), USA