This paper proposes the use of machine learning techniques to make storage systems more
reliable in the face of sector errors. Sector errors are partial drive failures, where individual …

This paper proposes the use of machine learning techniques to make storage systems more
reliable in the face of sector errors. Sector errors are partial drive failures, where individual …

Latent sector errors (LSEs) refer to the situation where particular sectors on a drive become
inaccessible. LSEs are a critical factor in data reliability, since a single LSE can lead to data …

Latent sector errors in disk drives affect only a few data sectors. They occur silently and are
detected only when the affected area is accessed again. If a latent error is detected while the …

The increasingly large demand for data storage has spurred on the development of systems
that rely on the aggregate performance of multiple hard drives. In many of these …

Modern storage systems orchestrate a group of disks to achieve their performance and
reliability goals. Even though such systems are designed to withstand the failure of …

A number of techniques have been proposed to reduce the risk of data loss in hard-drives,
from redundant disks (eg, RAID systems) to error coding within individual drives. Disk …

The storage system in large scale data centers is typically built upon thousands or even
millions of disks, where disk failures constantly happen. A disk failure could lead to serious …

Some statistical and machine learning methods have been proposed to build hard drive
prediction models based on the SMART attributes, and have achieved good prediction …

In recent years, high availability and reliability of data storage systems (DSS) have been
significantly threatened by soft errors occurring in storage controllers. Due to their specific …