Topic
Retrial queue
About: Retrial queue is a research topic. Over the lifetime, 784 publications have been published within this topic receiving 12354 citations.
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24 Jul 2010
TL;DR: Using matrix analytic techniques, the blocking probability of new calls and the dropping probability of handoff calls are obtained, the mean queue lengths of two types of calls.
Abstract: We consider that there are infinite positions in the orbit and N channels in the wireless cellular networks. For channel allocation, N1 (0 N1
01 Jan 2011
TL;DR: In this paper, two approaches to study the convergence in distribution of the busy period of the M/G/1 retrial queue have been proposed, relying on the modeling of Artalejo and Falin (1996) and an invariance principle for independent random variables.
Abstract: In this work, we propose two approaches to study the convergence in distribution of the busy period of the M/G/1 retrial queue. The first approach rely on the modeling of Artalejo and Falin (1996) and an invariance principle for independent random variables. In the second one, we use the evolution of the system in terms of idle periods and busy periods of the server and we conclude too with an Holderian invariance principle.
01 Oct 2018
TL;DR: A novel efficient analytical approach based on a semi-recursive algorithm for the numerical computation of the CTMC steady state probabilities resulted from a finite population CAC retrial queuing model that demonstrates that the consideration of cells with small size can achieve better performances in term of the call blocking probability.
Abstract: Small cell networks (SCNs) are the recent evolution of the cellular mobile networks. Based on the small-cell concept, SCNs aim to increase the data capacity and the subscriber’s population. Call admission control (CAC) is used in SCNs to prevent the system congestion and the service degradation for in-progress calls by restricting the access to the network. In the literature, almost all the existing works on CAC in cellular mobile networks with guard channels and repeated blocked calls propose a multi-server retrial queue model, which it is generally represented by a two-dimensional continuous time Markov chain (CTMC). For which, no analytical solution is available and only numerical approximation can be studied. In this paper, we propose a novel efficient analytical approach based on a semi-recursive algorithm for the numerical computation of the CTMC steady state probabilities resulted from a finite population CAC retrial queuing model. We represent using the retrial queue model a CAC scheme with multiple guard channels that consider repeated attempts of fresh blocked calls and impatience handover calls. In our model, the small-cells population is considered finite. In addition, we develop the principal stationary performance indices. The numerical results show that the proposed algorithm is substantially more accurate and achieves efficient computation. Also, demonstrates that the consideration of cells with small size can achieve better performances in term of the call blocking probability.
TL;DR: It is found that the performance measures are mainly affected by the two types of customers' arrivals and service patterns, but the retrial rate plays a less crucial role.
Abstract: In this paper, we consider the BMAP/PH/c retrial queue with two types of customers where the rate of individual repeated attempts from the orbit is modulated according to a Markov Modulated Poisson Process Using the theory of multi-dimensional asymptotically quasi-Toeplitz Markov chain, we obtain the algorithm for calculating the stationary distribution of the system Main performance measures are presented Furthermore, we investigate some optimization problems The algorithm for determining the optimal number of guard servers and total servers is elaborated Finally, this queueing system is applied to the cellular wireless network Numerical results to illustrate the optimization problems and the impact of retrial on performance measures are provided We find that the performance measures are mainly affected by the two types of customers' arrivals and service patterns, but the retrial rate plays a less crucial role