Convergence and limit of mean-value analysis algorithms

  • Authors:
  • Ágnes Bogárdi-Mészöly;Tihamér Levendovszky;Hassan Charaf;Ágnes Szeghegyi

  • Affiliations:
  • Budapest University of Technology and Economics, Department of Automation and Applied Informatics, Budapest, Hungary;Budapest University of Technology and Economics, Department of Automation and Applied Informatics, Budapest, Hungary;Budapest University of Technology and Economics, Department of Automation and Applied Informatics, Budapest, Hungary;Budapest University of Technology and Economics, Department of Automation and Applied Informatics, Budapest, Hungary

  • Venue:
  • ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
  • Year:
  • 2008

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Abstract

The performance of information systems is one of the most important and complicated consideration. Performance metrics can be predicted with the help of a proper performance model and an appropriate evaluation algorithm. In our work, the Mean-Value Analysis evaluation algorithm is enhanced based on the investigation of thread pools. With the enhanced performance evaluation algorithm the performance metrics of multi-tier information systems can be predicted much more accurate. In addition, the enhanced algorithm is experimentally validated. The goal of our work is the convergence and limit analysis of the original and the enhanced algorithms.