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Research on energy saving algorithm of datacenter in cloud computing system

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TLDR
The definition and characteristics of cloud computing are described, and the high energy consumption problem of cloud datacenter is focused, and a comparative analysis of the advantages, disadvantages and applicable scene of these algorithms are made.
Abstract
This paper briefly described the definition and characteristics of cloud computing,and focused the high energy consumption problem of cloud datacenter.Based on the classification of the energy saving algorithm,it researched the three kind of energy saving algorithms in a big way,including the energy saving algorithm based-DVFS,energy saving algorithm based-virtualization and the energy saving algorithm based-turn off/on of hosts,and made a comparative analysis of the advantages,disadvantages and applicable scene of these algorithms.Finally,it sumed up the further research problems for energy consumption management in cloud computing datacenter.

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Citations
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References
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Proceedings ArticleDOI

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Proceedings Article

Energy-aware server provisioning and load dispatching for connection-intensive internet services

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Journal ArticleDOI

Computing in the clouds

Aaron Weiss
TL;DR: This research presents a meta-service architecture that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of developing and deploying new types of services and applications.
Book ChapterDOI

Cost of Virtual Machine Live Migration in Clouds: A Performance Evaluation

TL;DR: In this paper, the authors evaluate the effects of live migration of virtual machines on the performance of applications running inside Xen VMs and show that, in most cases, migration overhead is acceptable but cannot be disregarded, especially in systems where availability and responsiveness are governed by strict Service Level Agreements.
Proceedings ArticleDOI

Energy Efficient Allocation of Virtual Machines in Cloud Data Centers

TL;DR: Evaluation results are presented showing that dynamic reallocation of VMs brings substantial energy savings, thus justifying further development of the proposed policy.
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