Dynamic thermal and IT resource management strategies for data center energy minimization

Abstract

Energy-hungry data centers attract researchers’ attention to energy consumption minimization–a challenge confronted by both industry and academia. To assure the server reliability, its instantaneous temperature is generally controlled within a preset threshold. Nonetheless, field studies indicated that the occasional violation of extreme temperature constraints hardly affect the system reliability in practice. Therefore, strictly restraining the server temperature may contribute to meaningless energy consumption. As a response to this limitation, this paper presents a dynamic control algorithm without violating the average temperature constraint. We formulate a “soft” Server Temperature-Constrained Energy Minimization (STCEM) problem, where the object function consists of IT and Heat Ventilation & Air Conditioner (HVAC) energy. Based on the Lyapunov optimization, two algorithms, i.e., linear and quadratic control policies, are proposed to approximately solve the STCEM problem. The non-negative weight parameter V is introduced to trade off the energy consumption against server temperature constraint. Furthermore, extensive simulations have been carried out to evaluate the system performance for the proposed controlled algorithms. The experimental results demonstrate that the quadratic control policy outperforms the linear counterpart on the STCEM problem. Specifically, the energy consumption and server temperature constraint are well balanced when V≈5000.