The energy consumption in data centers is drastically increasing and becoming a significant portion in the data center operating expenses. Enabling a sleep mode in the idle computing servers and network hardware is the most efficient method to avoid unnecessary power consumption. However, changes in the power modes introduce considerable delays. Moreover, inability to wake up a sleeping server immediately requires an availability of a pool of idle servers able to accommodate incoming load in the short term to prevent QoS degradation. In this paper we investigate the amount of computing servers and network hardware needed to accommodate different incoming load patters in the data centers. Furthermore, we propose to build these servers on energy efficient hardware, which is costly but can scale its power consumption with the offered load levels. The evaluation results show that the proposed methodology can save up to 750 per server per year on average. © 2013 IEEE.
Accounting for load variation in energy-efficient data centers
Kliazovich, Dzmitry;Arzo, Sisay T.;Granelli, Fabrizio;
2013-01-01
Abstract
The energy consumption in data centers is drastically increasing and becoming a significant portion in the data center operating expenses. Enabling a sleep mode in the idle computing servers and network hardware is the most efficient method to avoid unnecessary power consumption. However, changes in the power modes introduce considerable delays. Moreover, inability to wake up a sleeping server immediately requires an availability of a pool of idle servers able to accommodate incoming load in the short term to prevent QoS degradation. In this paper we investigate the amount of computing servers and network hardware needed to accommodate different incoming load patters in the data centers. Furthermore, we propose to build these servers on energy efficient hardware, which is costly but can scale its power consumption with the offered load levels. The evaluation results show that the proposed methodology can save up to 750 per server per year on average. © 2013 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione



