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Parallel Mining of Correlated Heavy Hitters

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Computational Science and Its Applications – ICCSA 2018 (ICCSA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10964))

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Abstract

We present a message-passing based parallel algorithm for mining Correlated Heavy Hitters from a two-dimensional data stream. To the best of our knowledge, this is the first parallel algorithm solving the problem. We show, through experimental results, that our algorithm provides very good scalability, whilst retaining the accuracy of its sequential counterpart.

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Acknowledgements

The authors would like to thank the Supercomputing Center of the Euro-Mediterranean Center on Climate Changes, Foundation for granting the access to the Athena supercomputer machine.

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Authors and Affiliations

  1. University of Salento, 73100, Lecce, Italy

    Marco Pulimeno, Italo Epicoco, Massimo Cafaro, Catiuscia Melle & Giovanni Aloisio

  2. Euro-Mediterranean Center on Climate Changes Foundation, 73100, Lecce, Italy

    Italo Epicoco, Massimo Cafaro & Giovanni Aloisio

Authors
  1. Marco Pulimeno
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  2. Italo Epicoco
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  3. Massimo Cafaro
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  4. Catiuscia Melle
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  5. Giovanni Aloisio
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Corresponding author

Correspondence to Massimo Cafaro .

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Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka shi, Fukuoka, Japan

    Bernady O. Apduhan

  9. Politecnico di Bari, Bari, Italy

    Eufemia Tarantino

  10. Myongji University, Yongin, Korea (Republic of)

    Yeonseung Ryu

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Pulimeno, M., Epicoco, I., Cafaro, M., Melle, C., Aloisio, G. (2018). Parallel Mining of Correlated Heavy Hitters. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10964. Springer, Cham. https://doi.org/10.1007/978-3-319-95174-4_48

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  • DOI: https://doi.org/10.1007/978-3-319-95174-4_48

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95173-7

  • Online ISBN: 978-3-319-95174-4

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