a two-tier energy-aware resource management for virtualized cloud computing system

Clicks: 96
ID: 147696
2016
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #94 of 121 articles by views in environmental pollution

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 121 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The economic costs caused by electric power take the most significant part in total cost of data center; thus energy conservation is an important issue in cloud computing system. One well-known technique to reduce the energy consumption is the consolidation of Virtual Machines (VMs). However, it may lose some performance points on energy saving and the Quality of Service (QoS) for dynamic workloads. Fortunately, Dynamic Frequency and Voltage Scaling (DVFS) is an efficient technique to save energy in dynamic environment. In this paper, combined with the DVFS technology, we propose a cooperative two-tier energy-aware management method including local DVFS control and global VM deployment. The DVFS controller adjusts the frequencies of homogenous processors in each server at run-time based on the practical energy prediction. On the other hand, Global Scheduler assigns VMs onto the designate servers based on the cooperation with the local DVFS controller. The final evaluation results demonstrate the effectiveness of our two-tier method in energy saving.
Reference Key
huang2016scientifica Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Wei Huang;Zhen Wang;Mianxiong Dong;Zhuzhong Qian
Journal environmental pollution
Year 2016
DOI
10.1155/2016/4386362
URL
http://dx.doi.org/10.1155/2016/4386362
Keywords
computer software

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.