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Compression Planner for Time Series Database with GPU Support

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Transactions on Large-Scale Data- and Knowledge-Centered Systems XV

Part of the book series: Lecture Notes in Computer Science ((TLDKS,volume 8920))

Abstract

Nowadays, we can observe increasing interest in processing and exploration of time series. Growing volumes of data and needs of efficient processing pushed research in new directions. This paper presents a lossless lightweight compression planner intended to be used in a time series database system. We propose a novel compression method which is ultra fast and tries to find the best possible compression ratio by composing several lightweight algorithms tuned dynamically for incoming data. The preliminary results are promising and open new horizons for data intensive monitoring and analytic systems.

P. Przymus: The project was partially funded by Marshall of Kuyavian-Pomeranian Voivodeship in Poland with the funds from European Social Fund (EFS) in the form of a PhD scholarships. “Krok w przyszłość – stypendia dla doktorantów V edycja” (Step in the future – PhD scholarships V edition).

K. Kaczmarski: The project was partially funded by National Science Centre, decision DEC-2012/07/D/ST6/02483.

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Notes

  1. 1.

    In this work we understand optimal compression as the best compression within available lightweight algorithms.

  2. 2.

    Note that this is a certain simplification, i.e. instead \(c_{re}(0,h_{re},\bar{D})\) where \(\bar{D}\) is dataset after removing all instances of dominant value.

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Author information

Authors and Affiliations

  1. Nicolaus Copernicus University, Toruń, Poland

    Piotr Przymus

  2. Warsaw University of Technology, Warsaw, Poland

    Krzysztof Kaczmarski

Authors
  1. Piotr Przymus
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  2. Krzysztof Kaczmarski
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Correspondence to Piotr Przymus .

Editor information

Editors and Affiliations

  1. IRIT, Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  2. FAW, University of Linz, Linz, Austria

    Josef Küng

  3. FAW, University of Linz, Linz, Austria

    Roland Wagner

  4. University of Genoa, Genoa, Italy

    Barbara Catania

  5. University of Genoa, Genoa, Italy

    Giovanna Guerrini

  6. LIPADE, Paris Descartes University, Paris, France

    Themis Palpanas

  7. Charles University, Prague, Czech Republic

    Jaroslav Pokorný

  8. Aristotle University of Thessalonik, Thessaloniki, Greece

    Athena Vakali

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Przymus, P., Kaczmarski, K. (2014). Compression Planner for Time Series Database with GPU Support. In: Hameurlain, A., et al. Transactions on Large-Scale Data- and Knowledge-Centered Systems XV. Lecture Notes in Computer Science(), vol 8920. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45761-0_2

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  • DOI: https://doi.org/10.1007/978-3-662-45761-0_2

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