Modeling the Impact of Disk Scrubbing on Storage System

One of characteristics of the rising cloud storage technology is low-cost and high reliability. A distinct benefit of disk scanning or scrubbing operation is identifying the potential failure sectors as early as possible, thus providing high reliability. Obviously, the higher the scrubbing frequency is, the higher the system reliability is. However, it may take a few hours for a scanning process to check the whole disk. In other words, the scrubbing process may result in a downtime or a lower system performance. Furthermore, the scrubbing process consumes energy. In order to reduce the impact of disk scrubbing on disk performance and energy consumption, system designers choose to scan the disk in a low frequency, which results in a lower reliability. Thus it is essential to design a good scrubbing scheme in a large scale storage system over long time horizons. In this paper, we present a novel scrubbing scheme to solve the challenge. In this scheme, an optimum scrubbing cycle is decided by keeping a balance between data loss cost, scrubbing cost, and disk failure rate. Our research shows how the data price and the scrubbing cost affect scrubbing frequency, and the scrubbing scheme is applicable for storage with inexpensive data. Our experiment shows that our scheme outperforms routine method 73.3% in cost and 40% in reliability.

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