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Evaluation of Cloud Service Reliability Based on Classified Statistics and Hierarchy Variable Weight

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A Correction to this article was published on 19 November 2019

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Abstract

With the rapid growth of Cloud Computing, more and more organizations choose cloud service to support their business. And the reliability of cloud service has been widely concerned. To better serve the use of cloud service as well as efficiently decide the reliability of cloud service, it is important to know how to deal with the evaluation. In this paper, we establish a cloud service reliability model. This model can be presented to solve the problems with cloud service reliability evaluation which is significantly affected by subjective factors and to further improve its scientific nature. Meanwhile, we proposed a method based on classified statistics and hierarchy variable weight to efficiently evaluate the cloud service reliability based on the model. The experimental results show that the model and method constructed in this paper can be used to efficiently evaluate the cloud service reliability through the classified processing and hierarchical division of subjective and objective characteristics/ subcharacteristics.

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Change history

  • 19 November 2019

    The Publisher regrets an error on the printed front cover of the October 2019 issue. The issue numbers were incorrectly listed as Volume 91, Nos. 10-12, October 2019. The correct number should be: "Volume 91, No. 10, October 2019"

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Authors and Affiliations

  1. State Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100010, China

    Ping Zhou, Luo-Ming Meng & Xue-Song Qiu

  2. China Electronics Standardization Institute, Beijing, 100007, China

    Ping Zhou, Ze-Sheng Wang, Zhi-Peng Wang & Zhi-Feng Chen

Authors
  1. Ping Zhou
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  2. Luo-Ming Meng
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  3. Xue-Song Qiu
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  4. Ze-Sheng Wang
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  5. Zhi-Peng Wang
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  6. Zhi-Feng Chen
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Correspondence to Ping Zhou.

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Zhou, P., Meng, LM., Qiu, XS. et al. Evaluation of Cloud Service Reliability Based on Classified Statistics and Hierarchy Variable Weight. J Sign Process Syst 91, 1115–1126 (2019). https://doi.org/10.1007/s11265-018-1407-2

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  • DOI: https://doi.org/10.1007/s11265-018-1407-2

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