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The cloud computing load forecasting algorithm based on wavelet support vector machine

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Published:31 January 2017Publication History

ABSTRACT

In this paper, we propose a model based on the wavelet support vector machine(WSVM), which combines the wavelet transform's advantage of analyzing the cycle and frequency of the input signal with the support vector machine's characteristic of nonlinear regression analysis, to model the task load in the cloud computing center. Then we propose a cloud computing load forecasting algorithm based on WSVM. Finally, we verify the forecasting results using the data set of Google cloud computing center. The results prove that the algorithm we proposed performs better comparing with the similar forecasting algorithms in forecasting effect and accuracy.

References

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      • Published in

        cover image ACM Other conferences
        ACSW '17: Proceedings of the Australasian Computer Science Week Multiconference
        January 2017
        615 pages
        ISBN:9781450347686
        DOI:10.1145/3014812

        Copyright © 2017 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 31 January 2017

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        ACSW '17 Paper Acceptance Rate78of156submissions,50%Overall Acceptance Rate204of424submissions,48%

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