Health Status Assessment and Failure Prediction for Hard Drives with Recurrent Neural Networks

IEEE Transactions on Computers

Volumn 65, Issue 11, 2016, Pages 3502-3508

  Xu, Chang ^a   Wang, Gang ^a   Liu, Xiaoguang ^a   Guo, Dongdong ^b   Liu, Tie Yan ^c  

^a NANKAI UNIVERSITY   (China)

^b Qihoo 360 Company   (China)

^c MICROSOFT RESEARCH ASIA   (China)

Author keywords

Hard drive failure prediction; health degree; recurrent neural networks; SMART

Indexed keywords

ARTIFICIAL INTELLIGENCE; DRIVES; FAULT TOLERANCE; FORECASTING; HARD DISK STORAGE; HEALTH; LEARNING SYSTEMS;

FAILURE PREDICTION METHOD; FAULT TOLERANCE TECHNIQUES; HARD DRIVE FAILURE PREDICTION; LARGE-SCALE STORAGE SYSTEMS; MACHINE LEARNING METHODS; REAL-WORLD DATASETS; RECURRENT NEURAL NETWORK (RNN); SMART;

RECURRENT NEURAL NETWORKS;

EID: 84994700810     PISSN: 00189340     EISSN: None     Source Type: Journal    
DOI: 10.1109/TC.2016.2538237     Document Type: Article

References (19)

1. K. V. Vishwanath and N. Nagappan, "Characterizing cloud computing hardware reliability, " in Proc. IEEE Symp. Cloud Comput., Jun. 2010, pp. 193-204.
2. B. Schroeder and G. A. Gibson, "Disk failures in the real world: What does an MTTF of 1;000;000 hours mean to you?" in Proc. Conf. File Storage Technol., 2007, pp. 1-16.
3. Q. Xin, E. L. Miller, D. D. E. Long, S. A. Brandt, T. Schwarz, W. Litwin, "Reliability mechanisms for very large storage systems, " in Proc. IEEE Conf. Mass Storage Syst. Technol., 2003, pp. 146-156.
4. J. F. Murray, G. F. Hughes, D. Schuurmans, "Machine learning methods for predicting failures in hard drives: A multiple-instance application, " J. Mach. Learn. Res., vol. 6, pp. 783-816, 2005.
5. G. Hamerly and C. Elkan, "Bayesian approaches to failure prediction for disk drives, " in Proc. Int. Conf. Mach. Learn., 2001, pp. 202-209.
6. G. F. Hughes, J. F. Murray, K. Kreutz-Delgado, C. Elkan, "Improved disk-drive failure warnings, " IEEE Trans. Rel., vol. 51, no. 3, pp. 350-357, 2002.
7. J. F. Murray, G. F. Hughes, K. Kreutz-Delgado, "Hard drive failure prediction using non-parametric statistical methods, " in Proc. Int. Conf. Artif. Neural Netw., 2003.
8. Y. Zhao, X. Liu, S. Gan, W. Zheng, "Predicting disk failures with HMM and HSMM based approaches, " in Proc. Adv Data Mining, Appl. Theoretical Aspects, 2010, pp. 390-404.
9. B. Zhu, G. Wang, X. Liu, D. Hu, "Proactive drive failure prediction for large scale storage systems, " in Proc. IEEE Symp. Mass Storage Syst. Technol., 2013, pp. 1-5.
10. Y. Wang, Q. Miao, M. Pecht, "Health monitoring of hard disk drive based on Mahalanobis distance, " in Proc. Prognostics Syst. Health Manag. Conf., 2011, pp. 1-8.
11. Y. Wang, Q. Miao, E. W. M. Ma, K.-L. Tsui, "Online anomaly detection for hard disk drives based on Mahalanobis distance, " IEEE Trans. Rel., vol. 62, no. 1, pp. 136-145, Mar. 2013.
12. T. Mikolov, S. Kombrink, L. Burget, J. Cernocky, S. Khudanpur, "Extensions of recurrent neural network language model, " in Proc. IEEE Int. Conf. Acoust., Speech Signal Process., May 2011, pp. 5528-5531.
13. T. Mikolov, M. Karafiat, L. Burget, J. Cernocky, S. Khudanpur, "Recurrent neural network based language model, " in Proc. INTERSPEECH, 2010, p. 3.
14. S. Kombrink, T. Mikolov, M. Karafit, L. Burget, "Recurrent neural network based language modeling in meeting recognition, " in Proc. INTERSPEECH, 2011, pp. 2877-2880.
15. M. Auli, M. Galley, C. Quirk, G. Zweig, "Joint language and translation modeling with recurrent neural networks, " Oct. 2013, pp. 1044-1054.
16. J. Li, X. Ji, Y. Jia, B. Zhu, "Hard drive failure prediction using classification and regression trees, " in Proc. IEEE/IFIP Int. Conf. Dependable Syst. Netw., 2014, pp. 383-394.
17. Y. Bengio, R. Ducharme, P. Vincent, C. Jauvin, "A neural probabilistic language model, " J. Mach. Learn. Res., vol. 3, pp. 1137-1155, 2003.
18. A. Graves, M. Liwicki, S. Fernandez, R. Bertolami, H. Bunke, J. Schmidhuber, "A novel connectionist system for unconstrained handwriting recognition, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 5, pp. 855-868, May 2009.
19. D. E. Rumelhart, G. E. Hinton, R. J. Williams, "Learning representations by back-propagating errors, " Nature, vol. 323, no. 6088, pp. 533-536, 1986.