As the adoption of Information and Communication Technology (ICT) tools in production and
service rendering sectors increases, the demand for digital data storage with large storage …

abstract Latent sector errors (LSEs) in disk drives cause significant outages, data loss, and
unreliability in largescale cloud storage systems, posing not only technical challenges but …

Storage systems have a strong need for substantially improving their error correction
capabilities, especially for long-term storage where the accumulating errors can exceed the …

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 …

The digital transformation disrupts the various professional domains in different ways,
though one aspect is common: the unified platform known as cloud computing. Corporate …

With the rapid growth in scale and complexity, today's enterprise storage systems need to
deal with significant amounts of errors. Existing proactive methods mainly focus on machine …

The purpose of the study is to design a cloud storage service to detect the maximum
probability of disrupted data blocks in a timely manner for any dynamic changes of …

The increasing popularity of cloud storage has led many organizations that dealing with
critical data (financial, medical, telecoms data) to consider moving data out of their data …

The ideal for cloud storage is to be self-managed, self-balanced and self-replicated, with
regular data checksums to account for the undetectable or mis-corrected error rates of …

Recognizing the impact from cluster recovery operations on performance and mean time to
recovery (MTTR) is essential to maintain service and availability objectives. Testing the …