MULTI-FACTOR CLOUD SERVICE STORAGE DEVICE ERROR PREDICTION

Systems and techniques for multi-factor cloud service storage device error prediction are described herein. A set of storage device metrics and a set of computing system metrics may be obtained. A feature set may be generated using the set of storage device metrics and the set of computing system me...

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Bibliographische Detailangaben
Hauptverfasser: JO ISAMU, LIN QINGWEI, SUI KAIXIN
Format: Patent
Sprache:chi ; eng
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Zusammenfassung:Systems and techniques for multi-factor cloud service storage device error prediction are described herein. A set of storage device metrics and a set of computing system metrics may be obtained. A feature set may be generated using the set of storage device metrics and the set of computing system metrics. Members of the feature set may be validated by evaluating a validation training dataset using the members of the feature set. A modified feature set may be created based on the validation. A storage device failure model may be created using the modified feature set. A storage device rating range may be determined by minimizing a cost of misclassification of a storage device. A set of storage devices to be labeled may be identified as having a high probability of failure. 本文中描述了用于多因素云服务存储设备错误预测的系统和技术。一组存储设备度量和一组计算系统度量可以被获取。特征集可以使用该一组存储设备度量和该一组计算系统度量而被生成。特征集的成员可以通过使用特征集的成员评估验证训练数据集而被验证。已修改特征集可以基于验证而被创建。存储设备故障模型可以使用已修改特征集而被创建。存储设备额定范围可以通过使存储设备的误分类成本最小化而被确定。待标记的一组存储设备可以被标识为具有高故障概率。