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Estimation and monitoring of traffic intensities with application to control of stochastic systems

Authors

  • Ying-Chao Hung,

    Corresponding author
    1. Department of Statistics, National Chengchi University, Taipei 11605, Taiwan
    • Correspondence to: Ying-Chao Hung, Department of Statistics, National Chengchi University, Taipei 11605, Taiwan.

      E-mail: hungy@nccu.edu.tw

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  • George Michailidis,

    1. Department of Statistics and Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109-1092, USA
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  • Shih-Chung Chuang

    1. Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu 30013, Taiwan
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Abstract

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.

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