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Erschienen in:
2020 | OriginalPaper | Buchkapitel
Use Machine Learning Methods to Predict Lifetimes of Storage Devices
verfasst von : Yingxuan Zhu, Bowen Jiang, Yong Wang, Tim Tingqiu Yuan, Jian Li
Erschienen in: Performance Evaluation and Benchmarking for the Era of Cloud(s)
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Abstract
Erase count is a key performance indicator of hard drives, and it shows the lifetime of a device. Analysis of erase counts helps us understand the performance of a device and prevent the failure of it. In this paper, a machine learning based framework is proposed to predict the curves of erase counts. Specifically, probabilities and erase-count curves of different hard drives are first calculated from training data. The probabilities are for deciding disk type in testing data. The erase-count curves from training data serve as references to testing data. Long short-term memory is utilized to model the erase-count difference between a reference device and a testing device, and to predict the lifetime of the testing device. Preliminary results of synthetic data show that our method can follow references and precisely predict erase counts.