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An energy-efficient process migration approach to reducing electric energy consumption in a cluster of servers

机译:一种节能的过程迁移方法,可减少服务器集群中的电能消耗

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In order to realise eco society, we have to reduce electric energy consumed by servers in a cluster. Clients issue requests of application processes to servers in a cluster. Here, application processes have to be efficiently performed on servers with respect to not only performance but also energy consumption. In this paper, we newly propose an energy-efficient process migration (EMG) approach to energy-efficiently performing application processes on servers. Here, processes on servers migrate to other servers so that the processes are more efficiently performed. We first discuss how to estimate the termination time of each current process on a server and the total electric energy consumption of a server to perform every current process. A process performed on a current server migrates to another server if the server is expected to consume smaller electric energy to perform the process than the current server and the deadline constraint on the process is satisfied on the server by using the estimation models. In the evaluation, we show the total energy consumption of servers is smaller and the average execution time of each process is shorter in the EMG algorithm than non-migration algorithms like the round robin and random algorithms.
机译:为了实现生态社会,我们必须减少集群中服务器消耗的电能。客户端向群集中的服务器发出应用程序请求。在此,不仅要在性能上而且还要在能耗上必须在服务器上有效地执行应用程序过程。在本文中,我们新提出了一种节能流程迁移(EMG)方法,以在服务器上高效执行应用程序流程。在此,服务器上的进程将迁移到其他服务器,以便更有效地执行进程。我们首先讨论如何估计服务器上每个当前进程的终止时间以及执行每个当前进程的服务器的总电能消耗。如果期望服务器消耗比当前服务器小的电能来执行该过程,并且使用估计模型在服务器上满足了该过程的最后期限约束,则在当前服务器上执行的过程将迁移到另一台服务器。在评估中,我们显示,与非迁移算法(例如循环算法和随机算法)相比,EMG算法中的服务器总能耗较小,每个进程的平均执行时间较短。

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