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Although queueing models in the mathematical field of queueing theory are mainly studied in the steady-state regime and practical applications are interested mostly in queues in transient situations subject to burst arrivals and congestion, their use is still justified as a first step towards a more complex and thorough analysis. In these practical applications, parameters such as the traffic intensity, which is the ratio between the arrival rate and service rate, are unknown and need to be estimated statistically. In this study, a Markovian arrival and deterministic single-server queueing system, known in Kendall notation as an M ∕ D ∕ 1 queueing model, is considered. This is one of the simplest queueing models with deterministic service time and may be seen as an approximation of a variety of applications in the performance evaluation of production management, telecommunications networks, and other areas. The main goal of this manuscript is to propose a methodology to determine the sample size for an M ∕ D ∕ 1 queueing system under the Bayesian setup by observing the number of customer arrivals during the service time of a customer. To verify the efficiency and efficacy of the proposed approach, an extensive set of numerical results is presented and discussed.

The paper is concerned with the problem of change point for the inter arrival time distribution for the M/M/1 queueing system by considering the number of customers present in the system. Bayesian estimators of traffic intensities, before the change $$(\rho _1)$$ and after the change $$(\rho _2)$$ , and the change point m are derived using the informative as well as non-informative priors under different loss functions. Finally a numerical example along with a practical example is given to illustrate the results.

Very often it is impracticable or costly to collect all information regarding the arrival times and service times of queue. In such a situation, it is therefore necessary to develop sampling plans ...

Problems of large sample estimation for the parameters in a single server queueing set up are discussed. The queueing system is observed over a continuous time interval (0,T] , where T is determined by a suitable stopping rule. The asymptotic properties of the maximum likelihood estimator from single server queues are studied using the martingale technique. An example with simulation study is given to illustrate the results.

The paper is concerned with the study of change point problem in the inter-arrival time and service time of single server queues. Maximum likelihood estimators of the parameters are derived. A test statistics has been developed and its properties have been studied.