Bayesian Forecasting of WWW Traffic on the Time Varying Poisson Model
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概要
- 論文の詳細を見る
Traffic forecasting from past observed traffic data with small calculation complexity has been one of important problems for planning of servers and networks. Focusing on World Wide Web (WWW) traffic as fundamental investigation, this paper would deal with Bayesian forecasting of network traffic on the time varying Poisson model from a viewpoint from statistical decision theory. Under this model, we would show that the forecasting estimate is obtained by simple arithmetic calculation with a known constant of time varying degree parameter and expresses real WWW traffic well from both theoretical and empirical points of view.
- 一般社団法人情報処理学会の論文
- 2009-07-06
著者
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Daiki Koizumi
Research Institute For Science And Engineering Waseda University
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Toshiyasu Matsushima
Department of Applied Mathematics, School of Fundamental Science and Engineering, Waseda University
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Shigeichi Hirasawa
Research Institute for Science and Engineering, Waseda University
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Toshiyasu Matsushima
Department Of Applied Mathematics School Of Fundamental Science And Engineering Waseda University
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Hirasawa Shigeichi
Waseda Univ.
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Shigeichi Hirasawa
Research Institute For Science And Engineering Waseda University
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