HCSIM: An indexing method for long-lived frequent block-level snapshot

Snapshot-based backup techniques can protect data from accidental and physical errors and support reliable storage. The long-lived frequent snapshot is low in search efficiency, because of the shared data between versions. Up to now there is no efficient indexing method for the long-lived frequent block-level snapshot. Adapting the block-level snapshot distributing features, this paper proposes a general-purpose two-dimensional indexing structure: Hierarchical Clustering Snapshot Indexing Method (HCSIM). The experimental results show that HCSIM can dramatically increase indexing storage efficiency than traditional temporal and spatial indexing structure Overlapping B+Tree. At the meantime, HCSIM can achieve better query efficiency in the context of long-lived snapshot management. The theoretical analysis exposes that HCSIM structure can achieve better balance between storage and query efficiency than nowadays block-level snapshot indexing method.