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

  • Matei Popovici
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7486)

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.

Keywords

temporal knowledge representation temporal logic high-performance computing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Matei Popovici
    • 1
  1. 1.POLITEHNICA University of BucharestBucharestRomania

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