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Energy Conservation Using Dynamic Voltage Frequency Scaling for Computational Cloud

机译:使用动态电压频率缩放进行计算云的节能

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摘要

Cloud computing is a new technology which supports resource sharing on a “Pay as you go” basis around the world. It provides various services such as SaaS, IaaS, and PaaS. Computation is a part of IaaS and the entire computational requests are to be served efficiently with optimal power utilization in the cloud. Recently, various algorithms are developed to reduce power consumption and even Dynamic Voltage and Frequency Scaling (DVFS) scheme is also used in this perspective. In this paper we have devised methodology which analyzes the behavior of the given cloud request and identifies the associated type of algorithm. Once the type of algorithm is identified, using their asymptotic notations, its time complexity is calculated. Using best fit strategy the appropriate host is identified and the incoming job is allocated to the victimized host. Using the measured time complexity the required clock frequency of the host is measured. According to that CPU frequency is scaled up or down using DVFS scheme, enabling energy to be saved up to 55% of total Watts consumption.
机译:云计算是一项新技术,支持“按需付费”的全球资源共享。它提供各种服务,例如SaaS,IaaS和PaaS。计算是IaaS的一部分,整个计算请求将通过云中的最佳功耗利用率得到有效满足。最近,开发了各种算法来降低功耗,甚至在此角度下也使用了动态电压和频率缩放(DVFS)方案。在本文中,我们设计了一种方法来分析给定云请求的行为并确定算法的关联类型。一旦算法的类型被确定,使用它们的渐近符号,就可以计算出其时间复杂度。使用最佳匹配策略,可以识别适当的主机,并将传入的作业分配给受害主机。使用所测量的时间复杂度,可以测量主机所需的时钟频率。据称,使用DVFS方案可以按比例放大或缩小CPU频率,从而可以节省多达总瓦数消耗55%的能量。

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