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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/9575

Title: Performance Evaluation of a Green Scheduling Algorithm for Energy Savings in Cloud Computing
Authors: Duy, Truong Vinh Truong
Sato, Yukinori
Inoguchi, Yasushi
Keywords: Energy Savings
Cloud
Green Scheduling
Issue Date: 2010-04
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Magazine name: 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW)
Start page: 1
End page: 8
DOI: 10.1109/IPDPSW.2010.5470908
Abstract: With energy shortages and global climate change leading our concerns these days, the power consumption of datacenters has become a key issue. Obviously, a substantial reduction in energy consumption can be made by powering down servers when they are not in use. This paper aims at designing, implementing and evaluating a Green Scheduling Algorithm integrating a neural network predictor for optimizing server power consumption in Cloud computing. We employ the predictor to predict future load demand based on historical demand. According to the prediction, the algorithm turns off unused servers and restarts them to minimize the number of running servers, thus minimizing the energy use at the points of consumption to benefit all other levels. For evaluation, we perform simulations with two load traces. The results show that the PP20 mode can save up to 46.3% of power consumption with a drop rate of 0.03% on one load trace, and a drop rate of 0.12% with a power reduction rate of 46.7% on the other.
Rights: Copyright (C) 2010 IEEE. Reprinted from 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW), , 2010, 1-8. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of JAIST's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
URI: http://hdl.handle.net/10119/9575
Material Type: publisher
Appears in Collections:e11-1. 会議発表論文 (Conference Papers)

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