在可扩展集群中选择服务器的能量感知算法

Hiroki Kataoka, A. Sawada, Dilawaer Duolikun, T. Enokido, M. Takizawa
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引用次数: 4

摘要

降低信息系统,特别是服务器集群的电能消耗是至关重要的。本文讨论了多cpu服务器的MLPCM(多cpu多级功耗)模型和MLCM(多cpu多级计算)模型。在本文中,我们提出了一种改进的全局能量感知(MEA)算法,用于在m个服务器集群中为进程选择服务器。在MEA算法中,如果服务器的总电能最小,则以计算复杂度O(m)选择要执行所有流程的服务器。我们对MEA算法进行了评估,结果表明,与其他算法相比,MEA算法不仅减少了服务器的总能耗,而且减少了进程的平均执行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy-Aware Algorithms to Select Servers in Scalable Clusters
It is critical to reduce the electric energy consumed in information systems, especially server clusters. In this paper, we discuss an MLPCM (multi-level power consumption with multiple CPUs) model and an MLCM (multi-level computation with multiple CPUs) model of a server with multiple CPUs. In this paper, we newly propose a modified globally energy-aware (MEA) algorithm to select a server for a process in a cluster of m servers. In the MEA algorithm, a server where a process all is to be performed is selected with computation complexity O(m) if the total electric energy of the servers is minimum. We evaluate the MEA algorithm and show not only the total electric energy consumption of the servers but also the average execution time of processes are reduced in the MEA algorithm compared with other algorithms.
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