Transient Analysis of Queueing Model

This paper deals with the study of Erlangian queueing system with time dependent framework. Under our study we fnd (i) the expected number of customers in the queue (ii) the expected waiting time before being served (iii) the expected time spent in the system (iv) the expected number of customers in the system. Customers arrive in the system in Poisson fashion with rate and served in arbitrary service time distribution with rate µ.The probability generating function technique and Laplace transform method have been used. The numerical computation has also been obtained for applicability of the model. Journal of the Institute of Engineering, 2015, 11(1): 165-171

On queueing systems by retrials

A general result for queueing systems with retrials is presented. This result relates the expected total number of retrials conducted by an arbitrary customer to the expected total number of retrials that take place during an arbitrary service time. This result is used in the analysis of a special system where two types of customer arrive in an independent Poisson fashion at a single-server service station with no waiting room. The service times of the two types of customer have independent general distributions with finite second moments. When the incoming customer finds the server busy he immediately leaves and tries his luck again after an exponential amount of time. The retrial rates are different for different types of customers. Expressions are derived for the expected number of retrial customers of each type.

On queueing systems by retrials

A general result for queueing systems with retrials is presented. This result relates the expected total number of retrials conducted by an arbitrary customer to the expected total number of retrials that take place during an arbitrary service time. This result is used in the analysis of a special system where two types of customer arrive in an independent Poisson fashion at a single-server service station with no waiting room. The service times of the two types of customer have independent general distributions with finite second moments. When the incoming customer finds the server busy he immediately leaves and tries his luck again after an exponential amount of time. The retrial rates are different for different types of customers. Expressions are derived for the expected number of retrial customers of each type.

An extension of Erlang's formulas which distinguishes individual servers

For a particular kind of finite-server loss system in which the number and identity of servers depends on the type of the arriving call and on the state of the system, the limits of the state probabilities (as t → ∞) are found for an arbitrary service-time distribution.

An extension of Erlang's formulas which distinguishes individual servers

For a particular kind of finite-server loss system in which the number and identity of servers depends on the type of the arriving call and on the state of the system, the limits of the state probabilities (as t → ∞) are found for an arbitrary service-time distribution.