Enabling Data-Deduplication-Assisted Data Relocation for Interlaced Magnetic Recording
Chen-Jui Tu, Shuo-Han Chen
Abstract
Interlaced Magnetic Recording (IMR) drives have been regarded as promising hard disk drives (HDDs) to meet the ever-growing storage demand in the post-AI era. Among various technologies, IMR drives achieve increased storage capacity by overlapping tracks in an interlaced fashion; however, updating data on overlapped tracks necessitates rewriting up to two tracks, which can degrade performance. Previous strategies have attempted to reduce track rewrites by either delaying the timing of overlapping based on storage space usage or relocating frequently updated data to non-overlapped tracks through update-frequency-based hot/cold data separation. In contrast, this paper proposes a novel approach that leverages data deduplication as a natural solution to the rewrite challenge in IMR drives. Unlike conventional hot/cold separation, this paper utilizes deduplication metadata, specifically reference counts, as a direct indicator for data relocation. The rationale behind the proposed approach is that deduplicated data, which remains static unless reference counts drop to one, can be stored or migrated to overlapped tracks without inducing future track rewrites. The proposed approach diverges from traditional frequency tracking methods by leveraging data deduplication information to guide data placement and reduce rewriting. Evaluation results show that the proposed scheme effectively reduces the accumulated read/write latency by on average compared with state-of-the-art data management on IMR drives with data deduplication enabled.
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