Variance Reduction Technique for Multi Network of Markovian Queue
Journal: International Journal of Science and Research (IJSR) (Vol.5, No. 10)Publication Date: 2016-10-05
Authors : Ankit Kaparwan; V. S. Singh; Jagdish C. Purohit;
Page : 432-435
Keywords : Point-estimation; confidence interval; finite horizon and steady-state simulation;
Abstract
Variance reduction technique that is particularly well suited for simulating rare events and, more specifically, estimating rare event probabilities. Properly applied, it often results in tremendous efficiency improvements compared to direct simulation schemes Markovian process is a process of decision making through Poisson arrivals and exponential service to facilitate easy analyzing and get usable results. It representing the number of customers in a system is known as a birth and death process, which is widely used in population models. The birth death terminology is used to represent increase and decrease in the population size. The corresponding events in queueing systems are arrivals and departures. In the present paper we consider the performance analysis of network of queues using variance reduction technique. A variance reduction technique essentially transform the underlying simulation model into a related one, the letter permitting more accurate estimation of the parameter of interest. The most variance reduction techniques typically reduce the variance by a constant factor and the exception to this rule is the importance sampling approach, which lead to dramatic variance reduction in many non-trivial cases of interest.
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