Sensitivity analysis for output performance measures in long-range dependent queueing system

Internet traffic has been shown to exhibit characteristics that are very different from traditional telephone network traffic such as long-range dependence (LRD). Therefore, performance analysis of queueing system in LRD traffic is needed to design reliable networks under the tremendous growth of Internet traffic. In this paper, we evaluate the sensitivity of input distribution on the output performance measures. We conduct a Monte Carlo simulation based on a designed experiment in order to relate four performance measures such as the mean and the expected maximum number of requests in queue, and the mean and the expected maximum time in queue to the degree of LRD in arrival, traffic intensities and the types of distributions in GI/G/1 queue. Experimental results show that mis-identification of input distributions has a significant effect on the output performances especially when one of the input distributions has LRD property. For such cases, Weibull distribution overestimated the output performances while lognormal distribution underestimated those of the LRD queues.