Effects of Data Scrubbing on Reliability in Storage Systems

Abstract

Silent data corruptions, which are induced by latent sector errors, phantom writes, DMA parity errors and so on, can be detected by explicitly issuing a read command to a disk controller and comparing the corresponding data with their checksums. Because some of the data stored in a storage system may not be accessed for a long time, there is a high chance of silent data corruption occurring undetected, resulting in data loss. Therefore, periodic checking of the entire data in a storage system, known as data scrubbing, is essential to detect such silent data corruptions in time. The errors detected by data scrubbing will be recovered by the replica or the redundant information maintained to protect against permanent data loss. The longer the period between data scrubbings, the higher the probability of a permanent data loss. This paper proposes a Markov failure and repair model to conservatively analyze the effect of data scrubbing on the reliability of a storage system. We show the relationship between the period of a data scrubbing operation and the number of data replicas to manage the reliability of a storage system by using the proposed model.