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Estimation and monitoring of traffic intensities with application to control of stochastic systems
Author(s) -
Hung YingChao,
Michailidis George,
Chuang ShihChung
Publication year - 2012
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.1961
Subject(s) - computer science , queueing theory , control (management) , traffic intensity , function (biology) , mathematical optimization , operations research , artificial intelligence , mathematics , computer network , evolutionary biology , biology
The development of optimal control strategies for many stochastic models relies on the observed traffic intensity. However, implementation of such control strategies is often infeasible because of high operating costs induced by the fluctuations of traffic flows. In this study, we propose a framework for estimating and monitoring the traffic intensities of stochastic systems. The framework does not require knowledge of any input traffic statistics, and it allows us to adaptively estimate the intensity function over time and simultaneously detect its significant changes so that the control strategy can be adjusted accordingly without requiring high operating costs. Finally, a canonical queueing system with various types of input traffic is used to evaluate the effectiveness of the proposed framework. Copyright © 2012 John Wiley & Sons, Ltd.