Fuzzy probabilities for web planning

  • Authors:

  • J. J. Buckley;K. Reilly;X. Zheng

  • Affiliations:

  • Department of Mathematics Birmingham, University of Alabama at Birmingham, 35294, Alabama, USA;Department of Computer and Information Sciences Birmingham, University of Alabama at Birmingham, 35294, Alabama, USA;Department of Computer and Information Sciences Birmingham, University of Alabama at Birmingham, 35294, Alabama, USA

  • Venue:
  • Soft Computing - A Fusion of Foundations, Methodologies and Applications
  • Year:
  • 2004

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Abstract

We apply our new approach to modeling uncertain probabilities to queuing theory and the optimal design of web servers. This involves using fuzzy, finite, regular Markov chains to determine the fuzzy steady state probabilities and then computing the fuzzy numbers for system performance. We first ignore revenues and costs in determining an optimal system and then we incorporate these factors for optimal design. Then we add two new phenomena associated with the web in our optimization models: “burstiness” and “long tailed distributions”.