期刊论文

Jiang, TM

英文

Future Generation Computer Systems

0167-739X

2023

148

460-471

10.1016/j.future.2023.05.020

This work is also done in Key Laboratory of Information Storage System and Ministry of Education of China . It is supported by the National Natural Science Foundation of China (key program) No. 62232007 , the National Natural Science Foundation of China No. 61902135 , the Natural Science Foundation of Hubei Province No. 2022CFB060 , the China Postdoctoral Science Foundation under Grant No. 2021M701367 , the Basic Scientific Research of China University under Grant No. CCNU21XJ020 and No. CCNU22QN016 , and the Ministry of Education - China Mobile Research Funding No. MCM20180406 .

本校为通讯机构

Disk failure prediction aims to predict upcoming disk failures in advance for high data reliability. There are numerous supervised machine learning methods that are successful in predicting disk failure using SMART properties as input. However, these approaches heavily rely on a substantial number of annotated failed disks, resulting in degraded prediction performance caused by scarce failed disks at the beginning, also known as the cold start problem. Inspired by the success achieved in Generative Adversarial Network (GAN) based anomaly detect...