Fuzzy based sequential learning for HDD health status prediction in data center

https://doi.org/10.53730/ijhs.v6nS2.5812

Authors

  • Naresh Kumar M MCA students at MEPCO Schlenk Engineering College, Sivakasi, Tamilnadu, India
  • Prasika L. Assistant Professor in the MCA department of MEPCO Schlenk Engineering College, Sivakasi, Tamilnadu, India

Keywords:

sequential learning, HDD failure, SMART, fuzzy ensemble learnin

Abstract

Data center is the essential part in maintaining data stores and IT systems in an enterprise. HDD (Hard Disk Drive) plays a crucial role in datacenter.The reliability of HDD is to be considered as an important factor.Prevention of Failure in HDD is significant for enabling security over data.In this paper, an Ensemble based sequential learning model was proposed to predict the failure of HDD at earliest.Sequential model learned the history of data and predicts the failure.It learned the pattern and predict the failures.In our approach, LSTM and GRU learning models are used for sequential learning. Ensemble learning was combined with these sequential model for predicting disk failure.The continous data from HDD was observed as SMART data and is used for constructing learning models to predict the results with an accuracy of  89.3%

 

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References

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Published

10-04-2022

How to Cite

Naresh Kumar, M., & Prasika, L. (2022). Fuzzy based sequential learning for HDD health status prediction in data center. International Journal of Health Sciences, 6(S2), 3261–3266. https://doi.org/10.53730/ijhs.v6nS2.5812

Issue

Section

Peer Review Articles