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Using Evolution Graphs for Describing Topology-Aware Prediction Models in Large Clusters

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Computational Logic in Multi-Agent Systems (CLIMA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7486))

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Abstract

We present and formally investigate a modelling method suitable for describing events and time-dependent properties and for performing possibly complex reasoning tasks regarding the evolution of dynamic domains. Our proposal consists of a distinguished data structure called evolution graph, and a logical language (\(\ensuremath{L_\ensuremath{\mathcal{H}}}\)) used for identifying temporal patterns in evolution graphs. First, we define and study the complexity of the model checking problem for our language. We then investigate the relation between our language and the well-known Computation Tree Logic (CTL), both in terms of complexity and expressive power. Finally, we apply our method for solving a well-known problem from High Performance Computing (HPC): the extraction of topology information from event logs produced by supercomputers.

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Author information

Authors and Affiliations

  1. POLITEHNICA University of Bucharest, Splaiul Independentei nr. 313, Bucharest, Romania, Postal Code 060042

    Matei Popovici

Authors
  1. Matei Popovici
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Liverpool, L69 3BX, Liverpool, UK

    Michael Fisher

  2. University of Luxembourg, 6 Rue Richard Coudenhove-Kalergi, 1359, Luxembourg, Luxembourg

    Leon van der Torre

  3. Department of Information and Computing Sciences, Utrecht University, Princetonplein 5, 3584 CC, Utrecht, The Netherlands

    Mehdi Dastani

  4. Queensland Research Laboratory, NICTA, 4067, St. Lucia, QLD, Australia

    Guido Governatori

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Popovici, M. (2012). Using Evolution Graphs for Describing Topology-Aware Prediction Models in Large Clusters. In: Fisher, M., van der Torre, L., Dastani, M., Governatori, G. (eds) Computational Logic in Multi-Agent Systems. CLIMA 2012. Lecture Notes in Computer Science(), vol 7486. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32897-8_8

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  • DOI: https://doi.org/10.1007/978-3-642-32897-8_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32896-1

  • Online ISBN: 978-3-642-32897-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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