Sensor Selection for IT Infrastructure Monitoring

  • Gergely János Paljak
  • Imre Kocsis
  • Zoltán Égel
  • Dániel Tóth
  • András Pataricza
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 23)


Supervisory control is the main means to assure a high level performance and availability of large IT infrastructures. Applied control theory is used in physical and virtualization based clustering, autonomic-, self-healing and cloud computing, but similar problems arise in any distributed environment.

The selection of a compact, but sufficiently characteristic set of control variables is one of the core problems both for design and run-time complexity. Most results in the literature are based on a single algorithm for variable selection, but our measurements indicate that no single algorithm can generate faithful estimates for all the different operational domains.

We propose to use a combination of different model extraction techniques on benchmark-like data logs. The main advantages of this multi-paradigm approach are twofold: it provides good parameter estimators for predictive control in a simple way; and supports the identification of the actual operational domain facilitating context-aware adaptive control, diagnostics and repair.


Autonomic computing control theory signal processing artificial intelligence benchmarking performance and performability control 


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Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2010

Authors and Affiliations

  • Gergely János Paljak
    • 1
  • Imre Kocsis
    • 1
  • Zoltán Égel
    • 1
  • Dániel Tóth
    • 1
  • András Pataricza
    • 1
  1. 1.Department of Measurement and Information SystemsBudapest University of Technology and EconomicsBudapestHungary

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