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PLR: A Benchmark for Probabilistic Data Stream Management Systems

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Intelligent Information and Database Systems (ACIIDS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7198))

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Abstract

Inherent imprecision of data streams in many applications leads to need for real-time uncertainty management. The new emerging Probabilistic Data Stream Management Systems (PDSMSs) are being developed to handle uncertainties of data streams in real-time. Many approaches have been proposed so far but there is no way to compare them regarding precision and efficiency. This problem motivated us to design an evaluation framework to compare performance and accuracy of PDSMSs with each other and also with probabilistic databases. In this paper, after a brief introduction to PDSMSs, we describe requirements and challenges for designing a PDSMS benchmark. Then, we present different parts of our framework including probabilistic data stream generator, queries, and result evaluator. Furthermore, we focus on implementation aspects and use our framework to evaluate effects of floating precision in our PDSMS prototype.

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Author information

Authors and Affiliations

  1. Computer Engineering Department, Iran University of Science and Technology, Tehran, Iran

    Armita Karachi, Mohammad G. Dezfuli & Mostafa S. Haghjoo

Authors
  1. Armita Karachi
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  2. Mohammad G. Dezfuli
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  3. Mostafa S. Haghjoo
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Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, No. 415, Chien-Kung Road, 80778, Kaohsiung, Taiwan

    Jeng-Shyang Pan

  2. Graduate Institute of Educational Measurement and Statistics, National Taichung University of Education, No. 140, Min-Shen Road, 40306, Taichung, Taiwan

    Shyi-Ming Chen

  3. Wrocław University of Technology, Wyb. Wyspiańskiego 27, 50-370, Wrocław, Poland

    Ngoc Thanh Nguyen

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Karachi, A., Dezfuli, M.G., Haghjoo, M.S. (2012). PLR: A Benchmark for Probabilistic Data Stream Management Systems. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Intelligent Information and Database Systems. ACIIDS 2012. Lecture Notes in Computer Science(), vol 7198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28493-9_43

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  • DOI: https://doi.org/10.1007/978-3-642-28493-9_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28492-2

  • Online ISBN: 978-3-642-28493-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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