Título: Using Deep Neural Networks for Failure Prediction in HDDs

Data: 29/11/2018 Horário: 15:30h Local: Sala de Seminários – Bloco 952

Resumo:

Several research has been done to propose early failure detection techniques for hard disk drives in order to improve storage systems availability and avoid data loss. Failure prediction in such circumstances would allow for the reduction of downtime costs through anticipated disk replacements. Many of the techniques proposed so far mainly perform incipient failure detection thus not allowing for proper planning of such maintenance tasks. In this work, we present several remaining useful life estimation approaches for hard disk drives based on SMART parameters. All models are based on Deep Neural Networks.

Banca:

• Prof. Dr. João Paulo Pordeus Gomes (MDCC/UFC - Orientador)
• Prof. Dr. Javam de Castro Machado (MDCC/UFC - Coorientador)
• Prof. Dr. José Maria da Silva Monteiro Filho (MDCC/UFC)
• Prof. Dr. Guilherme de Alencar Barreto (UFC)