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2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW) (2010)
Atlanta, GA, USA
Apr. 19, 2010 to Apr. 23, 2010
ISBN: 978-1-4244-6533-0
pp: 1-8
Truong Vinh Truong Duy , Graduate School of Information Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa, 923-1292 Japan
Yukinori Sato , Center for Information Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa, 923-1292 Japan
Yasushi Inoguchi , Center for Information Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa, 923-1292 Japan
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.
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CITATION

Y. Inoguchi, T. V. Duy and Y. Sato, "Performance evaluation of a Green Scheduling Algorithm for energy savings in Cloud computing," 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW), Atlanta, GA, USA, 2010, pp. 1-8.
doi:10.1109/IPDPSW.2010.5470908
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