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
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