Work

Bayesian Forecasting of WWW Traffic on the Time Varying Poisson Model

Year: 2009

Type: preprint

Abstract: Traffic forecasting from past observed traffic data with small calculation complexity is 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 estimated forecasting value is obtained by simple arithmetic calculation and expresses real WWW traffic well from both theoretical and empirical points of view.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.0906.3923

Authors: Koizumi, Daiki, Matsushima, Toshiyasu, Hirasawa, Shigeichi

Institutions: Waseda University, Waseda Research Institute for Science and Engineering

Language: English

Topic: Forecasting Techniques and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

Funders: Waseda University, Japan Society for the Promotion of Science

Award: Construction of Theory of Digital Analysis

OpenAlex ID: W1589247331

Cites: 6

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Related to: 10