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A Method of Reliability Assessment Based on Neural Network and Fault Data Clustering for Cloud with Big Data

机译:基于神经网络的可靠性评估方法和大数据的云故障数据聚类

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In the mobile clouds, the data size recorded in database software becomes large. Considering the software reliability of cloud computing with big data, it is important for the software managers to assess the relationship among the database software and cloud software, because the cloud software collaborate closely with the database software by using the internet network. In this paper, we propose a method of software reliability assessment based on the fault data clustering and neural network in cloud computing environment with big data. We perform a cluster analysis for the software fault data by using k-means clustering. Also, we propose the estimation method of the cumulative numbers of detected faults based on the neural network by using the results of cluster analysis. Moreover, we show several numerical examples of software reliability assessment in the cloud computing environment with big data.
机译:在移动云中,数据库软件中记录的数据大小变大。考虑到大数据云计算的软件可靠性,软件管理员很重要,以评估数据库软件和云软件之间的关系,因为云软件通过使用Internet网络与数据库软件密切合作。在本文中,我们提出了一种基于大数据的云计算环境中的故障​​数据聚类和神经网络的软件可靠性评估方法。我们使用k均值群集对软件故障数据进行集群分析。此外,我们通过使用集群分析结果提出了基于神经网络的检测到故障累积数的估计方法。此外,我们在具有大数据的云计算环境中显示了多个数字示例。

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