Abstract
Traffic intensity is an important measure for assessing performance of a queueing system. In this paper, we propose a consistent and asymptotically normal estimator (CAN) of intensity for a queueing system with distribution-free interarrival and service times. Using this estimator and its estimated variance, a 100(1 − α)% asymptotic confidence interval of the intensity is constructed. Also, four bootstrap approaches—standard bootstrap, Bayesian bootstrap, percentile bootstrap, and bias-corrected and accelerated bootstrap are also applied to develop the confidence intervals of the intensity. A comparative analysis is conducted to demonstrate performances of the five confidence intervals of the intensity for a queueing system with short run data.
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Ke, JC., Chu, YK. Comparison on five estimation approaches of intensity for a queueing system with short run. Comput Stat 24, 567–582 (2009). https://doi.org/10.1007/s00180-008-0146-4
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DOI: https://doi.org/10.1007/s00180-008-0146-4