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

机译:云数据中心基于多服务器休假排队理论的节能策略

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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.
机译:能源消耗是云数据中心日益关注的问题,因为服务器利用率不足会导致大量电能浪费。因此,提高服务器利用率以实现最佳能源利用现在已成为迫在眉睫的问题。我们提出了一种基于多服务器休假排队理论的节能策略,该策略可以在组之间切换服务器的睡眠状态。该策略同时包含同步和异步策略。当空闲服务器的数量达到给定阈值时,空闲服务器将作为一组同步进入睡眠模式。不同的工作负载导致服务器组异步睡眠。我们采用策略将数据中心建模为M / M / H休假排队系统,并构建二维连续时间马尔可夫链来制定排队系统。使用强大的矩阵几何方法,我们获得了系统状态的平稳概率分布。我们使用理论和模拟实验的结果来估计我们方法的性能。该结果对于研究云数据中心的电源性能折衷非常有价值。

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