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Cloud computing system risk estimation and service selection approach based on cloud focus theory

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Abstract

The main cloud computing service providers usually provide cross-regional and services of Crossing Multi-Internet Data Centers that supported with selection strategy of service level agreement risk constraint. But the traditional quality of service (QoS)-aware Web service selection approach cannot ensure the real-time and the reliability of services selection. We proposed a cloud computing system risk assessment method based on cloud theory, and generated the five property clouds by collecting the risk value and four risk indicators from each virtual machine. The cloud backward generator integrated these five clouds into one cloud, according to the weight matrix. So the risk prediction value is transferred to the risk level quantification. Then we tested the Web service selection experiments by using risk assessment level as QoS mainly constraint and comparing with LRU and MAIS methods. The result showed that the success rate and efficiency of risk assessment with cloud focus theory Web services selection approaches are more quickly and efficient.

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Authors and Affiliations

  1. School of Software, Xiamen University, Xiamen, China

    Fan Lin, Wenhua Zeng, Lvqing Yang, Yue Wang, Shufu Lin & Jiasong Zeng

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  1. Fan Lin
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  2. Wenhua Zeng
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  3. Lvqing Yang
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  5. Shufu Lin
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Correspondence to Fan Lin.

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Lin, F., Zeng, W., Yang, L. et al. Cloud computing system risk estimation and service selection approach based on cloud focus theory. Neural Comput & Applic 28, 1863–1876 (2017). https://doi.org/10.1007/s00521-015-2166-7

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