Fuzzy Based Web Server Workload Modeling and Prediction

  • Chin Wen Cheong


In this paper, Web server workload is modelled by considering two most significant metrics, namely the burstiness factor and the bandwidth utilisation. The integration of the workload metrics are accomplished by using a fuzzy inference system(FIS) to lessen the complexity of the metrics relation. Due to the fluctuating of WWW requests, the utilisation states are viewed as a series of stochastic processes. The fuzzy Markovian prediction is study in two manners, firstly the utilisation states and secondly the Markovian property. The results of fuzzy approaches perform a more appropriate comparison


Membership Function Fuzzy Inference System Utilisation State Fuzzy State State Probability Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London 2002

Authors and Affiliations

  • Chin Wen Cheong
    • 1
  1. 1.FOSEEMultiMedia UniversityMalaccaMalaysia

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