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- W3080836056 abstract "Data deduplication saves storage space by identifying and removing repeats in the data stream. In this paper, we provide an information-theoretic analysis of the performance of deduplication algorithms with data streams where repeats are not exact. We introduce a source model in which probabilistic substitutions are considered. Two modified versions of fixed-length deduplication are studied and proven to have performance within a constant factor of optimal with the knowledge of repeat length. We also study the variable-length scheme and show that as entropy becomes smaller, the size of the compressed string vanishes relative to the length of the uncompressed string." @default.
- W3080836056 created "2020-09-01" @default.
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- W3080836056 date "2020-06-01" @default.
- W3080836056 modified "2023-10-18" @default.
- W3080836056 title "Data Deduplication with Random Substitutions" @default.
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- W3080836056 doi "https://doi.org/10.1109/isit44484.2020.9174380" @default.
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