• DocumentCode
    2415442
  • Title

    A neural network approach to system performance analysis

  • Author

    Gruen, Robert ; Kubota, Toshiro

  • Author_Institution
    VC3 Inc., Columbia, SC, USA
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    349
  • Lastpage
    354
  • Abstract
    Neural networks are used in a wide variety of situations to solve complex problems. Some of the categories for which neural networks are used include: prediction software, classification algorithms, data association environments, data conceptualization environments, and data filtering problems. This work described in this paper implements a neural network that spans both the prediction and data association problems. The neural network approach to system performance analysis takes performance data from computer systems and uses a Kohonen based neural network to analyze the performance data and attempts to find bottlenecks in the computer system. The data performance analysis results are present as line graphs that can be interpreted by computer experts to determine bottlenecks within the computer system, and can intelligently suggest upgrades to improve any subsystem that suffers from poor performance. The aim of this work is to provide a "proof of concept" for use in IT assessments, but can also be applied to any situation involving computer performance analysis
  • Keywords
    data analysis; performance evaluation; self-organising feature maps; IT assessments; Kohonen based network; VC3; bottlenecks; computer system; data association; neural network; system performance analysis; Classification algorithms; Computer networks; Data analysis; Filtering algorithms; Intelligent systems; Neural networks; Performance analysis; Prediction algorithms; Software algorithms; System performance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SoutheastCon, 2002. Proceedings IEEE
  • Conference_Location
    Columbia, SC
  • Print_ISBN
    0-7803-7252-2
  • Type

    conf

  • DOI
    10.1109/.2002.995618
  • Filename
    995618