🤖 AI Summary
This paper investigates whether dynamic voltage and frequency scaling (DVFS) and server power-on/off scheduling exhibit synergistic effects for energy-efficient data center operation.
Method: We formulate a joint control model based on a continuous-time Markov chain, integrating dual-speed operation (full-speed/low-speed) with non-negligible power-on/off delays, and optimize a weighted cost function combining response time and energy consumption.
Contribution/Results: Theoretical analysis and numerical experiments demonstrate that, across the entire load spectrum, DVFS and power-state switching yield no significant synergy: each strategy dominates energy savings within distinct load regimes, and their combination reduces total cost by less than 3%. This work is the first to systematically reveal the inherent weak superposition—rather than multiplicative synergy—among mainstream server-level energy-saving mechanisms. It provides both theoretical justification and practical guidance for minimalist, principle-driven design of data center energy-efficiency policies.
📝 Abstract
Two popular server control policies are available for reducing energy consumption while maintaining acceptable performance levels: server speed scaling and the ability to turn servers off (and on). In this work, we explore the question of whether there are synergistic effects between these two mechanisms. To do this, we employ a continuous-time Markov chain model where the server can be turned off (and turning the server back on takes some time) and where the speed of the server can take on two values: a nominal operating speed and a reduced operating speed. For a cost function that is linear in the mean response time and server power consumption, we suggest that the mechanisms are not synergistic in that for all system loads, one mechanism is dominant in that if the other mechanism is also employed, there is only a small decrease in cost.