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2013, Nonlinear Analysis: Real World Applications
We consider a single server retrial queue with waiting places in service area and three classes of customers subject to the server breakdowns and repairs. When the server is unavailable, the arriving class-1 customer is queued in the priority queue with infinite capacity whereas class-2 customer enters the retrial group. The class-3 customers which are also called negative customers do not receive service. If the server is found serving a customer, the arriving class-3 customer breaks the server down and simultaneously deletes the customer under service. The failed server is sent to repair immediately and after repair it is assumed as good as new. We study the ergodicity of the embedded Markov chains and their stationary distributions. We obtain the steady-state solutions for both queueing measures and reliability quantities. Moreover, we investigate the stochastic decomposition law, the busy period of the system and the virtual waiting times. Finally, an application to cellular mobile networks is provided and the effects of various parameters on the system performance are analyzed numerically.
2020
This paper deals with an unreliable server having three phases of heterogeneous service on the basis of M/G/1 queueing system. We suppose that customers arrive and join the system according to a Poisson’s process with arrival rate λ. When the server is working with any phase of service, it may breakdown at any instant. After breakdown, when the server is sent for repair then server stops its service and arrival customers are waiting for repair, which we may called as waiting period of the server. This waiting time stands for delay time/delay repair. In this model, first we derive the joint probability distribution for the server. Secondly, we derive the probability generating function of the stationary queue size distribution at a departure epoch as a classical generalisation of Pollaczek Khinchin formula. Third, we derive Laplace Stieltjes transform of busy period distribution and waiting time distribution. Finally, we obtain some important performance measures and reliability anal...
Discrete and Continuous Models and Applied Computational Science
In this investigation, we consider an M/G/1 queue with general retrial times allowing balking and server subject to breakdowns and repairs. In addition, the customer whose service is interrupted can stay at the server waiting for repair or leave and return while the server is being repaired. The server is not allowed to begin service on other customers until the current customer has completed service, even if current customer is temporarily absent. This model has a potential application in various fields, such as in the cognitive radio network and the manufacturing systems, etc. The methodology is strongly based on the general theory of stochastic orders. Particularly, we derive insensitive bounds for the stationary distribution of the embedded Markov chain of the considered system.
Applied Mathematical Modelling, 2009
This paper deals with the steady-state behaviour of an M/G/1 queue with an additional second phase of optional service subject to breakdowns occurring randomly at any instant while serving the customers and delayed repair. This model generalizes both the classical M/G/1 queue subject to random breakdown and delayed repair as well as M/G/1 queue with second optional service and server breakdowns. For this model, we first derive the joint distributions of state of the server and queue size, which is one of chief objectives of the paper. Secondly, we derive the probability generating function of the stationary queue size distribution at a departure epoch as a classical generalization ofPollaczek-Khinchin formula. Next, we derive Laplace Stieltjes transform of busy period distribution and waiting time distribution. Finally, we obtain some important performance measures and reliability indices of this model. Choudhury and Paul [5] investigated such a model under Bernoulli feedback mechanism. In this context Krishnakumar and Arivudainambi in [6] obtained the explicit expression for transient probabilities for this type of finite capacity model M/G/1/1 Bernoulli feedback queue and M/G/1/1 queue with unreliable server . Recently, Wang [8] investigated such a model with the assumption that the server is subject to breakdowns and repairs, and some critical reliability indices are obtained. More recently, Ke [9] extended the result for a multi-optional service system where concept of setup time is also introduced.
Quality Technology & Quantitative Management, 2017
In this paper, we study the steady state behaviour of an M/G/1 queue with two types of general heterogeneous service and optional repeated service subject to server's breakdowns occurring randomly at any instant while serving the customers and delayed repair. We assume that customers arrive to the system according to a Poisson process with rate 'λ' and the server provides two types of general heterogeneous service. At the beginning of a service, a customer has the option to choose any one type of service. After completion of either type of service, the customer has the further option to repeat the same type of service. For this model, we first derive the joint distribution of state of the server and queue size by considering both elapsed and remaining time, which is one of the objectives of this paper. Secondly, we derive the probability generating function of the stationary queue size distribution at departure epoch. Next, we derive Laplace-Stieltjes transform of busy period distribution and waiting time distribution. Finally, we obtain some important performance measure and reliability indices of this model.
Indian journal of science and technology, 2022
Objective: This study considered a system of retrial queues with two types of customers: high-priority and low-priority. This study deals to find the time dependent probabilities of exact number of arrivals and departures from the system when server is free or busy. Numerical solution and graphical representation will also be presented. Method: For this model, we solved difference differential equations recursively and used Laplace transformation to obtain the transient state probabilities of exact number of arrivals and departures from the system when server is free or busy. Findings: Timedependent probabilities of exact number of arrivals (primary arrivals, arrivals in high priority queue, arrivals in low priority queue) in the system and exact number of departures (primary departures, departures from high priority queue, departures from low priority queue) from the system by a given time for when the server is idle and when the server is busy are obtained. Various interesting performance measures along with some special cases are also obtained. Conversion of two state model into single state model was discussed. Numerical illustrations are also presented using MATLAB programming along with the busy period probabilities of the system and server. Novelty: In past research, models considered arrivals and departures from the orbit whereas in present model arrivals and departures from the system are studied along with the concept of retrial and priority customers. Applications: Priority retrial queues are used in many applications like real time systems, operating systems, manufacturing system, simulation and medical service systems.
Computers & Operations Research, 2010
A repairable queueing model with a two-phase service in succession, provided by a single server, is investigated. Customers arrive in a single ordinary queue and after the completion of the first phase service, either proceed to the second phase or join a retrial box from where they retry, after a random amount of time and independently of the other customers in orbit, to find a position for service in the second phase. Moreover, the server is subject to breakdowns and repairs in both phases, while a start-up time is needed in order to start serving a retrial customer. When the server, upon a service or a repair completion finds no customers waiting to be served, he departs for a single vacation of an arbitrarily distributed length. The arrival process is assumed to be Poisson and all service and repair times are arbitrarily distributed. For such a system the stability conditions and steady state analysis are investigated. Numerical results are finally obtained and used to investigate system performance.
Fourth International Conference on Advances in Information Processing and Communication Technology - IPCT 2016, 2016
We consider an M X /G/1 queuing system with breakdown and repairs, where batches of customers are assumed to arrive in the system according to a compound poisson process. While the server is being repaired, the customer in service either remains the service position or enters a service orbit and keeps returning, after repair the server must wait for the customer to return. The server is not allowed to accepte new customers until the customer in service leaves the system. We find a stability condition for this system. In the steady state the joint distribution of the server state and queue length is obtained, and some performance mesures of the system, such as the mean number of customers in the retrial queue and waiting time, and some numerical results are presented to illustrate the effect of the system parameters on the developed performance measures. Keywords-batch arrival, break down, repair. I. Introduction Retrial queuing systems have been widely used to model many practical problems arising in telephone switching systems, telecommunication networks, and computer systems. The main characteristic of these queues is that a customer who find the sever busy upon arrival joins the retrial group called orbit to repeat his request for service after some random time. For a systematic account of the fundamental methods and results on this topic the reader can refer to the survey papers of (
Entropy, 2019
A flexible single-server queueing system is considered in this paper. The server adapts to the system size by using a strategy where the service provided can be either single or bulk depending on some threshold level c. If the number of customers in the system is less than c, then the server provides service to one customer at a time. If the number of customers in the system is greater than or equal to c, then the server provides service to a group of c customers. The service times are exponential and the service rates of single and bulk service are different. While providing service to either a single or a group of customers, the server may break down and goes through a repair phase. The breakdowns follow a Poisson distribution and the breakdown rates during single and bulk service are different. Also, repair times are exponential and repair rates during single and bulk service are different. The probability generating function and linear operator approaches are used to derive the ...
International Journal of Operational Research, 2010
Communications in Computer and Information Science, 2015
In this paper we study a single-server Markovian retrial queueing system with non-reliable server and threshold-based recovery policy. The arrived customer finding a free server either gets service immediately or joins a retrial queue. The customer at the head of the retrial queue is allowed to retry for service. When the server is busy, it is subject to breakdowns. In a failed state the server can be repaired with respect to the threshold policy: the repair starts when the number of customers in the system reaches a fixed threshold level. Using a matrix-analytic approach we perform a stationary analysis of the system. The optimization problem with respect to the average cost criterion is studied. We derive expressions for the Laplace transforms of the waiting time. The problem of estimation and confidence interval construction for the fully observable system is studied as well.
OPSEARCH, 2012
In this paper, we consider a single server Markovian queueing system with a finite buffer. In addition to a Poisson stream of positive arrivals we assume that there is a also a Poisson stream of negative arrivals into the system. These negative arrivals which may be called as catastrophes may occur at any instant of time, whether the server is idle or busy. The time dependent performance measures and the busy period of the system are discussed. The corresponding steady state results are derived. We present a few numerical examples to illustrate the behavior of the time dependent probabilities, the time dependent expected system size and the time dependent variance of the system size distribution.
International Journal of Advanced Trends in Computer Science and Engineering
Retrial queues have been widely used to model many problems arising in telephone switching systems, telecommunication networks, computer networks and computer systems, etc.. In this paper an M x /G/1 retrial queue with two phase services, discouragement and general setup time is being studied where the server is subject to breakdown during service. Primary customers join the system according to Poisson process and receive the service immediately if the server is available upon arrival. Otherwise, they enter a retrial orbit with some probability and are queued in the orbit. They repeat their demand after some random interval of time. The customers are allowed to balk upon arrival. All the customers who join the queue have to undergo the first essential service, whereas only some of them demand for the second optional service. Using generating function approach and supplementary variable method, the steady state solutions for some queueing and reliability measures of the system are ob...
Journal of Mathematical Sciences, 2006
Queueing systems with repeated attempts have wide practical use in designing telephone switching systems, telecommunication networks, computer networks, and computer systems, etc. For a systematic account of the fundamental methods and results and, furthermore, an accessible classified bibliography on this topic, the interested reader is referred to, for example, and the references therein.
Queueing Systems - Theory and Applications, 2001
Negative arrivals are used as a control mechanism in many telecommunication and computer networks. In the paper we analyze multiserver retrial queues; i.e., any customer finding all servers busy upon arrival must leave the service area and re-apply for service after some random time. The control mechanism is such that, whenever the service facility is full occupied, an exponential timer is activated. If the timer expires and the service facility remains full, then a random batch of customers, which are stored at the retrial pool, are automatically removed. This model extends the existing literature, which only deals with a single server case and individual removals. Two different approaches are considered. For the stable case, the matrix-analytic formalism is used to study the joint distribution of the service facility and the retrial pool. The approximation by more simple infinite retrial model is also proved. In the overloading case we study the transient behaviour of the trajectory of the suitably normalized retrial queue and the long-run behaviour of the number of busy servers. The method of investigation in this case is based on the averaging principle for switching processes.
RAIRO - Operations Research, 2013
This paper describes an unreliable server batch arrival retrial queue with two types of repair and second optional service. The server provides preliminary first essential service (FES) to the primary arriving customers or customers from retrial group. On successful completion of FES, the customer may opt for second optional service (SOS) with probability α. The server is subject to active break downs. The customer under FES (or SOS) during the failure decides, with probability q, to join the orbit(impatient customer) and, with complementary probability p, to remain in the server for repair in order to conclude his remaining service (patient customer). Both service and repair times are assumed to have general distribution. It is considered that the repair time of server during the presence of patient customer and the repair time of the server while the customer (impatient customer) joining the orbit due to failure, are different. For this queueing system, the orbit and system size distributions are obtained. Reliability of the proposed model is analysed. Some particular cases are also discussed. Other performance measures are also obtained. The effects of several parameters on the system are analysed numerically.
The paper studies a queuing model with Poisson arrival process and bulk service. The server serves the customers in batches of fixed size b, and the service time is assumed to be exponentially distribution. The model is analyzed to find the steady-state distribution of the number of customers stranded following each service. The approach adopted is based on discrete-time Markov chains, instead of Laplace transforms that is usually used in literature. A simulation study is carried out to estimate the expected number of stranded customers at any point of time, its variance and the downside risk for given values of the system parameters.
2014
Here we will study bulk service to customer under optimal operation of a single removable and non-reliable server in Markovian queueing system under steady-state conditions. The decision maker can turn a server on at customer’s arrival or off at service completion. Here it is assumed that the server may breakdown only if working and requires repair at repair facility. Inter-arrival and service time distributions of the customers are assumed to be exponentially distributed. Breakdown and repair time distributions of the server are assumed to be exponentially distributed. The following cost structure is incurred to be system; a holding cost for each customer in the system per unit time, cost per unit time when a server fails, and fixed costs for turning the server on or off. The expected cost function per unit time is developed to obtain the optimal operating policy at minimum cost.
This paper deals with a single server retrial queueing system in which customers arrive according to poisson fashion with state dependent rates. An arriving customer enters into service immediately on finding the server free; otherwise the customer enters into a retrial orbit and repeatedly attempts to access the server at independent and identically distributed intervals. We study the classical and constant retrial policy in accordance with the discipline to access the server from the orbit. The service interruption due to server breakdown is taken into consideration. The repairman repairs the server in m-phases and also requires general distributed set up time before starting repair of 1 st phase. The life-time and phase repair time of the server are assumed to be according exponential and general distributed, respectively. We perform the steady state analysis of the model using supplementary variable technique and Laplace transform; then employ the probability generating function approach to derive expressions for various performance measures. Finally, numerical illustration is given to explore the effect of various parameters on the system performance.
—In this paper we consider an M/M/1 queueing system with non-reliable server. When the server is in normal state, the service error (or failure) occurs according to a Poisson process. In the error state, the server needs to be repaired at a repair facility with exponential repair time according to the threshold policy. The repair starts only when the number of customers in the system reaches some prespecified threshold level q ≥ 1. We perform a steady-state analysis of the continuous-time Markov chain describing the system behavior and calculate optimal threshold level to minimize the long-run average losses given by the cost structure.
OPSEARCH, 2015
The investigation deals with the steady-state behavior of a batch arrival retrial queue with multi-optional services and phase repair under Bernoulli vacation schedule. The customers enter the system in batches and are admitted following Bernoulli admission control policy. The incoming customers are forced to join the retrial group if they find the server unavailable. The customers are served in two phases viz. first essential service (FES) followed by second optional services (SOS). The server is unreliable and if fails, it is repaired in d-compulsory phases so as to become as good as before failure. The server may go for a vacation after each service completion following Bernoulli vacation schedule or it may continue serving the next customer. By applying the embedded Markov chain method, we establish the ergodicity condition for the system. The steady-state formulae for some queueing measures are established by evaluating the generating functions of queue length distribution. The cost function of the system has also been formulated. Finally, the effects of various parameters on the performance of the system have been examined numerically.
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