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Energy-Efficient Virtualisation of Threads in a Server Cluster

机译:服务器群集中线程的节能高效虚拟化

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It is critical to reduce the electric power consumed by servers in a cluster in order to realize eco society. In our previous studies, the multi-level power consumption (MLPC) model of a server with a multi-thread CPU, the power consumption of the server is proposed and the globally energy-aware (GEA) algorithm is discussed to select a server for each process in a cluster. Here, not only the total electric energy consumption of all the servers but also the ratio of the basic electric energy consumed by the servers to the total electric energy consumption can be reduced in a cluster. However, the GEA algorithm is not scalable since every server is checked to find a server for each process in a cluster. In this paper, we newly propose a scalable energy-aware (SEA) algorithm to select a server for a process. Here, some number of servers are first randomly selected in a cluster and one server is then selected in the selected servers by the GEA algorithm. We evaluate the SEA 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 SEA algorithm compared with other algorithms.
机译:为了实现生态社会,减少集群中服务器消耗的电力至关重要。在我们之前的研究中,提出了具有多线程CPU的服务器的多级功耗(MLPC)模型,提出了该服务器的功耗,并讨论了全局能源感知(GEA)算法来选择用于以下目的的服务器集群中的每个进程。在这里,不仅可以降低所有服务器的总电能消耗,而且还可以减少服务器消耗的基本电能与总电能消耗之比。但是,GEA算法不可扩展,因为要检查每个服务器以找到集群中每个进程的服务器。在本文中,我们新提出了一种可伸缩的能源感知(SEA)算法,以选择用于流程的服务器。在这里,首先在集群中随机选择一些服务器,然后通过GEA算法在所选服务器中选择一个服务器。我们评估了SEA算法,并显示与其他算法相比,SEA算法不仅减少了服务器的总电能消耗,而且还减少了进程的平均执行时间。

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