Lossless Compression of Time Series Data with Generalized Deduplication

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    Abstract

    To provide compressed storage for large amounts of time series data, we present a new strategy for data deduplication. Rather than attempting to deduplicate entire data chunks, we employ a generalized approach, where each chunk is split into a part worth deduplicating and a part that must be stored directly. This simple principle enables a greater compression of the often similar, non-identical, chunks of time series data than is the case for classic deduplication, while keeping benefits such as scalability, robustness, and on-the-fly storage, retrieval, and search for chunks. We analyze the method's theoretical performance, and argue that our method can asymptotically approach the entropy limit for some data configurations. To validate the method's practical merits, we finally show that it is competitive when compared to popular universal compression algorithms on the MIT-BIH ECG Compression Test Database.
    OriginalsprogEngelsk
    Titel2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings
    ForlagIEEE
    Publikationsdato2019
    Artikelnummer9013957
    ISBN (Elektronisk)978-1-7281-0962-6
    DOI
    StatusUdgivet - 2019
    Begivenhed2019 IEEE Global Communications Conference - Waikoloa, HI, USA, Waikoloa, USA
    Varighed: 9 dec. 201913 dec. 2019
    https://globecom2019.ieee-globecom.org/

    Konference

    Konference2019 IEEE Global Communications Conference
    LokationWaikoloa, HI, USA
    Land/OmrådeUSA
    ByWaikoloa
    Periode09/12/201913/12/2019
    Internetadresse

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    • Scale-loT

      Lucani Rötter, D. E. (Deltager)

      01/01/201831/12/2022

      Projekter: ProjektForskning

    • Starting Grant

      Lucani Rötter, D. E. (Deltager)

      Starting Grant

      01/02/201701/01/2020

      Projekter: ProjektForskning

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