MATEC Web of Conferences
Volume 65, 20162016 The International Conference on Nanomaterial, Semiconductor and Composite Materials (ICNSCM 2016)
|Number of page(s)||4|
|Section||Composites and Polymer Materials|
|Published online||06 July 2016|
Research on the Prediction Model of CPU Utilization Based on ARIMA-BP Neural Network
1 Liaoning Software Testing Center, Shenyang, China
2 College of Information Science & Technology Engineering, Northeastern University, Shenyang, China
a Corresponding author: email@example.com
The dynamic deployment technology of the virtual machine is one of the current cloud computing research focuses. The traditional methods mainly work after the degradation of the service performance that usually lag. To solve the problem a new prediction model based on the CPU utilization is constructed in this paper. A reference offered by the new prediction model of the CPU utilization is provided to the VM dynamic deployment process which will speed to finish the deployment process before the degradation of the service performance. By this method it not only ensure the quality of services but also improve the server performance and resource utilization. The new prediction method of the CPU utilization based on the ARIMA-BP neural network mainly include four parts: preprocess the collected data, build the predictive model of ARIMA-BP neural network, modify the nonlinear residuals of the time series by the BP prediction algorithm and obtain the prediction results by analyzing the above data comprehensively.
© Owned by the authors, published by EDP Sciences, 2016
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