Chapter 5. Mining for Misconfigured Machines in Grid Systems

  1. Werner Dubitzky
  1. Noam Palatin1,
  2. Arie Leizarowitz1,
  3. Assaf Schuster2 and
  4. Ran Wolff2

Published Online: 22 JUN 2009

DOI: 10.1002/9780470699904.ch5

Data Mining Techniques in Grid Computing Environments

Data Mining Techniques in Grid Computing Environments

How to Cite

Palatin, N., Leizarowitz, A., Schuster, A. and Wolff, R. (2009) Mining for Misconfigured Machines in Grid Systems, in Data Mining Techniques in Grid Computing Environments (ed W. Dubitzky), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470699904.ch5

Editor Information

  1. Biomedical Sciences Research Institute, University of Ulster, Coleraine, United Kingdom

Author Information

  1. 1

    Technion — Israel Institute of Technology, Department of Mathematics, Haifa, Israel

  2. 2

    Technion — Israel Institute of Technology, Department of Computer Science, Haifa, Israel

Publication History

  1. Published Online: 22 JUN 2009
  2. Published Print: 14 NOV 2008

ISBN Information

Print ISBN: 9780470512586

Online ISBN: 9780470699904

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Keywords:

  • Grid Monitoring System (GMS);
  • grid system misconfigured machine mining;
  • knowledge discovery process - acquiring;
  • pre-processing and storing data;
  • system data acquisition - intrusive and non-intrusive;
  • GMS ontology - a job;
  • a pool and matchmaking;
  • data analysis;
  • Distributed HilOut algorithm;
  • GMS using Condor DAGman;
  • large grid system misconfigured machine detection

Summary

This chapter contains sections titled:

  • Introduction

  • Preliminaries and related work

  • Acquiring, pre-processing and storing data

  • Data analysis

  • The GMS

  • Evaluation

  • Conclusions and future work

  • References