This paper considers a retrial queueing model for a base station in cellular networks where fresh calls and handover calls are available. Fresh calls are initiated from the cell of the base station. On the other hand, a handover call has been connecting to a base station and moves to another one. In order to keep the continuation of the communication, it is desired that an available channel in ...

GERAN (GSM-EDGE Radio Access Network) operators have traditionally used the Erlang B formula to estimate the number of signalling channels on a per-cell basis. Thus, it is assumed that the network behaves as a loss system with Poisson arrivals. However, the presence of automatic retrial mechanisms and correlated arrivals in these channels suggests that these assumptions might not be valid. This...

Consider a single server retrial queueing system with pre-emptive priority service and single working vacation in which two types of customers arrive in a Poisson process with arrival rates ?1 for low and ?2 for high priority customers. We assume that regular service times follow an exponential distribution with parameters μ1 and μ2 correspondingly. The retrial is introduced for low priority cu...

The interest in retrial queueing systems mainly lies in their application to telephone systems. This paper studies multiserver retrial queueing systems with n servers. The arrival process is a quite general point process. An arriving customer occupies one of the free servers. If upon arrival all servers are busy, then the customer waits for his service in orbit, and after a random time retries ...

Queueing models are widely used to establish stochastic models for QoS analysis of different communication environments. In [1] the authors created a queueing model to evaluate a sensor network environment with two quality classes of sources. The “Emergency” class represents the sources of very important communication (e.g. fire alarm), and the “Normal” class represents the standard communicati...

We analyze and compare three (s,S) inventory systems with positive service time and retrial of customers. In all of these systems, arrivals of customers form a Poisson process and service times are exponentially distributed. When the inventory level depletes to s due to services, an order of replenishment is placed. The lead-time follows an exponential distribution. In model I, an arriving cust...

This paper deals with the role of performance modeling tools. It introduces 3 major tool development centers and shows how a given tool can be applied to investigate the performance of a finite-source retrial queueing system.

We consider the single server constant retrial queue with a Poisson arrival process and exponential service and retrial times. This system has not waiting space, so the customers that find the server busy are forced to abandon the system, but they can leave their contact details. Hence, after a service completion, the server seeks for a customer among those that have unsuccessfully applied for ...

This paper models a call center as a Markovian queue with multiple servers, where customer balking, impatience, and retrials are modeled explicitly. The resulting queue is analyzed both in a stationary and non-stationary setting. For the stationary setting a fluid approximation is proposed, which overcomes the computational burden of the continuous time markov chain analysis, and which is shown...

This paper describes a discrete-time retrial queue and shows how importance sampling simulations can be applied for estimating the probability of large orbit content and the overflow fraction of primary calls.