Reducing Data Center Energy Consumption via Coordinated Cooling and Load Management

Abstract

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.

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