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- W2499004860 abstract "Data centers are growing rapidly in recent years. Data centers consume a huge amount of power, therefore how to save power is a key issue. Accurately predicting the power of virtual machine (VM) is significant to schedule VMs in different physical machines (PMs) to save power. Current researches rarely consider the impact of workload on this prediction. This paper studies the power prediction of VM under the multi-VM environment, with consideration of the impact of PMs’ workload. A RBF neural network approach is proposed to predict the VM’s power. Experiments show that the proposed approach is effective for VM’s power prediction and can achieve average error less than 2 %, which is smaller than those of comparative models." @default.
- W2499004860 created "2016-08-23" @default.
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- W2499004860 date "2016-01-01" @default.
- W2499004860 modified "2023-10-06" @default.
- W2499004860 title "Predicting Virtual Machine’s Power via a RBF Neural Network" @default.
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- W2499004860 doi "https://doi.org/10.1007/978-3-319-41009-8_40" @default.
- W2499004860 hasPublicationYear "2016" @default.
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