BaNHFaP: A Bayesian Network Based Failure Prediction Approach for Hard Disk Drives
Iago C. Chaves, Manoel Rui P. Paula, Lucas G. M. Leite, Lucas P. Queiroz, João P. P. Gomes, Javam C. Machado · 2016
A Hard Disk Drive (HDD) failure may lead to serious consequences for users and companies. Hence, predicting failures in HDDs became a topic that attracted much attention in recent years. Monitoring a HDD status can provide information about its degradation, so as to let the user or a system manager know about a failure before it happens, preventing loss of information. In this paper, we propose a failure prediction method using a Bayesian Network. Our method uses the deterioration over time of a HDD, calculated via SMART (SelfMonitoring Analysis and Reporting Technology) attributes, for predicting eventual failures. To demonstrate practical usefulness, this method was applied to a dataset consisting of 49,056 hard drives from Backblaze's data centers. The proposed method has improved the mean and median quadratic errors in 28.3% and 17.6% respectively in comparison with a baseline model.