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Cloud Computing. First International Conference, CloudComp 2009 Munich, Germany, October 19–21, 2009 Revised Selected Papers

Research Article

Proactive Software Rejuvenation Based on Machine Learning Techniques

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  • @INPROCEEDINGS{10.1007/978-3-642-12636-9_13,
        author={Dimitar Simeonov and D. Avresky},
        title={Proactive Software Rejuvenation Based on Machine Learning Techniques},
        proceedings={Cloud Computing. First International Conference, CloudComp 2009 Munich, Germany, October 19--21, 2009 Revised Selected Papers},
        proceedings_a={CLOUDCOMP},
        year={2012},
        month={5},
        keywords={proactive rejuvenation virtualisation machine learning techniques feature selection sparsity software aging (memory leaks) validation},
        doi={10.1007/978-3-642-12636-9_13}
    }
    
  • Dimitar Simeonov
    D. Avresky
    Year: 2012
    Proactive Software Rejuvenation Based on Machine Learning Techniques
    CLOUDCOMP
    Springer
    DOI: 10.1007/978-3-642-12636-9_13
Dimitar Simeonov1,*, D. Avresky1,*
  • 1: IRIANC
*Contact email: simeonov.dimitar@gmail.com, autonomic@irianc.com

Abstract

This work presents a framework for detecting anomalies in servers leading to crash such as memory leaks in aging systems and proactively rejuvenating them.

Keywords
proactive rejuvenation virtualisation machine learning techniques feature selection sparsity software aging (memory leaks) validation
Published
2012-05-28
http://dx.doi.org/10.1007/978-3-642-12636-9_13
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