Data Mining Meets Performance Evaluation: Fast Algorithms for Modeling Bursty Traffic

@inproceedings{Wang2002DataMM,
  title={Data Mining Meets Performance Evaluation: Fast Algorithms for Modeling Bursty Traffic},
  author={Mengzhi Wang and Ngai Hang Chan and Spiros Papadimitriou and Christos Faloutsos and Tara M. Madhyastha},
  booktitle={ICDE},
  year={2002}
}
Network, web, and disk I/O traffic are usually bursty, self-similar [9, 3, 5, 6] and therefore can not be modeled adequately with Poisson arrivals[9]. However, we do want to model these types of traffic and to generate realistic traces, because of obvious applications for disk scheduling, network management, web server design. Previous models (like fractional Brownian motion, ARFIMA etc) tried to capture the ‘burstiness’. However the proposed models either require too many parameters to fit and… CONTINUE READING
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