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An intelligent analysis and prediction model for on-demand cloud computing systems

Authors :
Xiuju Fu
Yongqing Zhu
Rick Siow Mong Goh
Lipo Wang
Xiaorong Li
Source :
IJCNN
Publication Year :
2014
Publisher :
IEEE, 2014.

Abstract

In this paper, an intelligent model for analyzing and predicting cloud computing resource utilization is proposed to enhance on-demand services in cloud computing systems. The model is with the capability to discover active users and mine the system storage utilization patterns. This model is also with learning capabilities to adapt the dynamics in the cloud computing platform by capturing changing patterns of system storage utilization, and it employs data mining means for computing the practical model to be used for prediction and providing inputs for intelligent management in the on-demand cloud computing system. We have evaluated the proposed analysis and prediction model in a cloud computing platform. High prediction accuracies of 95% and 86% have been achieved in 1-day ahead and 7-day ahead system utilization prediction, respectively.

Details

Database :
OpenAIRE
Journal :
2014 International Joint Conference on Neural Networks (IJCNN)
Accession number :
edsair.doi...........69ca236ec377610438d3cef0aa41aa48
Full Text :
https://doi.org/10.1109/ijcnn.2014.6889875