An energy-saving strategy based on multi-server vacation queuing theory in cloud data center

Energy consumption is a growing concern in cloud data centers because underutilization of servers results in significant wasted power. Thus, improving server utilization for optimal energy use is now an urgent issue. We propose an energy-saving strategy based on multi-server vacation queuing theory that switches servers between on and sleep in groups. The strategy incorporates both synchronous and asynchronous strategies. When the number of idle servers reaches to a given threshold, idle servers enter sleep mode synchronously as a group. Varying workloads cause groups of servers to sleep asynchronously. We model the data center with our strategy as an M/M/H vacation queuing system and construct a two-dimensional continuous-time Markov chain to formulate the queuing system. Using a powerful matrix-geometric method, we obtain the stationary probability distribution for the system states. We use results from theoretical and simulated experiments to estimate the performance of our approach. The results are valuable for studying the power-performance trade-off in cloud data centers.