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Discrete-time queueing models find a large number of applications as they are used in modeling queueing systems arising in digital platforms like telecommunication systems and computer networks. In this paper, we analyze an infinite-buffer queueing model with discrete Markovian arrival process. The units on arrival are served in batches by a single server according to the general bulk-service rule, and the service time follows general distribution with service rate depending on the size of the batch being served. We mathematically formulate the model using the supplementary variable technique and obtain the vector generating function at the departure epoch. The generating function is in turn used to extract the joint distribution of queue and server content in terms of the roots of the characteristic equation. Further, we develop the relationship between the distribution at the departure epoch and the distribution at arbitrary, pre-arrival and outside observer’s epochs, where the first is used to obtain the latter ones. We evaluate some essential performance measures of the system and also discuss the computing process extensively which is demonstrated by some numerical examples.

We consider an extended form of the MX/M/c queue with two types of server groups: Static as well as dynamic (which turn on/off in a state-dependent manner) servers. The two server groups may have homogenous or non-homogenous service rates. The model is further extended to feature setup and delayed-off times, finite capacity, and k staffing levels. This class of queues is solved via the difference equations approach, which addresses narratives in the literature and achieves higher numerical efficiency than the direct method. While the model of this queueing system is not new, the methodology for solving it is. Comparisons between our model and classic queues are provided followed by concluding remarks, including a summary of key observations.

A simple and complete solution to determine the distributions of queue lengths at different observation epochs for the model GIX/Geo/c/N is presented. In the past, various discrete-time queueing models, particularly the multi-server bulk-arrival queues with finite-buffer have been solved using complicated methods that lead to results in a non-explicit form. The purpose of this paper is to present a simple derivation for the model GIX/Geo/c/N that leads to a complete solution in an explicit form. The same method can also be used to solve the GIX/Geo/c/N queues with heavy-tailed inter-batch-arrival time distributions. The roots of the underlying characteristic equation form the basis for all distributions of queue lengths at different time epochs. All queue-length distributions are in the form of sums of geometric terms.

We present analytic expressions (in terms of roots of the underlying characteristic equation) for the steady-state distributions of the number of customers for the finite-state queueing model G e o...

This paper presents the distribution of the number of customers served during a busy period for special cases of the Geo/G/1 queue when initiated with m customers. We analyze the system under the assumptions of a late arrival system with delayed access and early arrival system policies. It is not easy to invert the functional equation for the number of customers served during a busy period except for the simple case Geo/Geo/1 queue, as stated by several researchers. Using the Lagrange inversion theorem, we give an elegant solution to this equation. We find the distribution of the number of customers served during a busy period for various service-time distributions such as geometric, deterministic, binomial, negative binomial, uniform, Delaporte, discrete phase-type and interrupted Bernoulli process. We compute the mean and variance of these distributions and also give numerical results. Due to the clarity of the expressions, the computations are very fast and robust. We also show that in the limiting case, the results tend to the analogous continuous-time counterparts.

This paper deals with a single server queueing system where the waiting space is limited. The server serves the customer in batches. The arrival process is considered to be renewal type and the services are considered to be correlated which has been presented by a continuous-time batch Markovian service process (C-BMSP). Distribution of the system length at pre-arrival instant of a customer and at an arbitrary-epoch have been determined for this queueing system. These probability distributions have been used for obtaining the blocking probability of an arbitrary customer, expected system-length, expected waiting time of an arbitrary customer in the system, and several other important performance measures. This model may find application in queueing systems involving inventory where delay in demand may lead to perishing of goods due to long wait in the system. Also, a profit function has been derived for such a queueing model to maximize the profit from the system for certain model parameters. Finally, assuming that the inter-arrival time follows phase-type distribution, a few numerical examples have been presented in the form of graphs and tables.

This paper presents analytically explicit results for the distribution of the number of customers served during a busy period for special cases of the M/G/1 queues when initiated with m customers. The functional equation for the Laplace transform of the number of customers served during a busy period is widely known, but several researchers state that, in general, it is not easy to invert it except for some simple cases such as M/M/1 and M/D/1 queues. Using the Lagrange inversion theorem, we give an elegant solution to this equation. We obtain the distribution of the number of customers served during a busy period for various service-time distributions such as exponential, deterministic, Erlang-k, gamma, chi-square, inverse Gaussian, generalized Erlang, matrix exponential, hyperexponential, uniform, Coxian, phase-type, Markov-modulated Poisson process, and interrupted Poisson process. Further, we also provide computational results using our method. The derivations are very fast and robust due to the lucidity of the expressions.

This paper deals with a renewal input finite-buffer single-server queue, where the arrivals occur in batches and the server serves the customers singly. It is assumed that the inter-batch arrival times are generally distributed and the successive service times are correlated. The correlated single-service process is exhibited by a continuous-time Markovian service process (C-MSP). As the buffer capacity N (including the one in service) is finite, the partial-batch rejection policy is considered here. Steady-state distributions at different epochs, namely pre-arrival and arbitrary epochs are obtained. These distributions are used to obtain some important performance measures, e.g. the blocking probability of the first, an arbitrary, and the last customer of a batch, the average number of customers in the system and the mean waiting time in the system. The proposed analysis is based on the roots of a characteristic equation which is derived from the balance equations of an embedded Markov chain at pre-arrival epochs of a batch. For this non-renewal service finite-buffer queueing model, we implement a novel as well as simple procedure for deriving the characteristic equation and then finding the stationary probability vectors in terms of the roots of the characteristic equation. Finally, some numerical results are presented in the form of tables for the case of a phase-type inter-batch arrival distribution.

This paper deals with the finite-buffer single server vacation queues with batch Markovian arrival process (BMAP). The server follows gated-limited service discipline, i.e., the server can serve a maximum of L customers out of those that are waiting at the start of the busy period or all the waiting customers, whichever is minimum. It has been assumed that the server can take only one vacation, i.e., if no customers are found at the end of a vacation, the server remains idle until a batch of customers arrives. The service time and vacation time distributions are considered to possess rational Laplace–Stieltjes transform. The queue-length distribution at post-departure, arbitrary, and pre-arrival epochs has been obtained. Various performance measures like mean queue-length, mean waiting time of an arbitrary customer, and mean length of busy and idle periods have been derived for this model. Numerical results have been presented based on the analysis done.

This article gives closed-form analytic expressions as well as a computational analysis of the stationary system-length distribution for the renewal-input, bulk-arrival, and multi-server continuous-time queueing model. The service times are equal to the constant D for any customer. The queueing model may be denoted as G I X / D / c queue. Using the steady-state equations, the system-length probability generating function is derived. Subsequently, by inverting this probability generating function the stationary system-length distribution is obtained using the roots of a characteristic equation. Next, a similar analysis for the corresponding multi-server queueing model with batch Markovian arrival process ( B M A P ) is carried out using the roots of a characteristic equation associated with the vector generating function of the system-length distribution. The distribution function of the stationary actual waiting-time for the first customer of an arrival batch in a B M A P / D / c queue is also derived. Some numerical implementation of the procedure for the G I X / D / c and B M A P / D / c queues is performed. Numerical values for the expected system length and waiting time are also obtained.

We give analytically explicit solutions for the distribution of the number of customers served during a busy period for the \begin{document}$ M^X/PH/1 $\end{document} queues when initiated with \begin{document}$ m $\end{document} customers. When customers arrive in batches, we present the functional equation for the Laplace transform of the number of customers served during a busy period. Applying the Lagrange inversion theorem, we provide a refined result to this functional equation. From a phase-type service distribution, we obtain the distribution of the number of customers served during a busy period for various special cases such as exponential, Erlang-k, generalized Erlang, hyperexponential, Coxian, and interrupted Poisson process. The results are exact, rapid and vigorous, owing to the clarity of the expressions. Moreover, we also consider computational results for several service-time distributions using our method. Phase-type distributions can approximate any non-negative valued distribution arbitrarily close, making them a useful practical stochastic modelling tool. These distributions have eloquent properties which make them beneficial in the computation of performance models.

This paper deals with a batch arrival infinite-buffer single server queue. The interbatch arrival times are generally distributed and arrivals are occurring in batches of random size. The service process is correlated and its structure is presented through a continuous-time Markovian service process (C-MSP). We obtain the probability density function (p.d.f.) of actual waiting time for the first and an arbitrary customer of an arrival batch. The proposed analysis is based on the roots of the characteristic equations involved in the Laplace-Stieltjes transform (LST) of waiting times in the system for the first, an arbitrary, and the last customer of an arrival batch. The corresponding mean sojourn times in the system may be obtained using these probability density functions or the above LSTs. Numerical results for some variants of the interbatch arrival distribution (Pareto and phase-type) have been presented to show the influence of model parameters on the waiting-time distribution. Finally, a simple computational procedure (through solving a set of simultaneous linear equations) is proposed to obtain the “R” matrix of the corresponding GI/M/1-type Markov chain embedded at a prearrival epoch of a batch.

This paper presents an alternative steady-state solution to the discrete-time Geo/G/1/N + 1 queueing system using roots. The analysis has been carried out for a late-arrival system using the imbedded Markov chain method, and the solutions for the early arrival system have been obtained from those of the late-arrival system. Using roots of the associated characteristic equation, the distributions of the numbers in the system at various epochs are determined. We find a unified approach for solving both finite- and infinite- buffer systems. We investigate the measures of effectiveness and provide numerical illustrations. We establish that, in the limiting case, the results thus obtained converge to the results of the continuous-time counterparts. The applications of discrete-time queues in modeling slotted digital computer and communication systems make the contributions of this paper relevant.

The previous studies pertaining to the queues Geo/G/1 and Geo/G/1/N involve light-tailed distributions for service time. However, due to applications of heavy-tailed distributions in computer science and financial engineering, these distributions are used for service time. This article provides a simple and computationally efficient solution to the queues Geo/G/1 and Geo/G/1/N involving heavy-tailed distributions for service times.

We consider an infinite buffer single server queue wherein batch interarrival and service times are correlated having a bivariate mixture of rational (R) distributions, where R denotes the class of distributions with rational Laplace–Stieltjes transform (LST), i.e., ratio of a polynomial of degree at most n to a polynomial of degree n. The LST of actual waiting time distribution has been obtained using Wiener–Hopf factorization of the characteristic equation. The virtual waiting time, idle period (actual and virtual) distributions, as well as inter-departure time distribution between two successive customers have been presented. We derive an approximate stationary queue-length distribution at different time epochs using the Markovian assumption of the service time distribution. We also derive the exact steady-state queue-length distribution at an arbitrary epoch using distributional form of Little’s law. Finally, some numerical results have been presented in the form of tables and figures.

We consider a finite-buffer single-server queue with batch Markovian arrival process. In the case of finite-buffer batch arrival queue, there are different customer rejection/acceptance strategies such as partial batch rejection, total batch rejection, and total batch acceptance policy. We consider partial batch rejection strategy throughout our paper. We obtain queue length distributions at various epochs such as pre-arrival, arbitrary, and post-departure as well as some important performance measures, like probability of loss for the first, an arbitrary, and the last customer of a batch, mean queue lengths, and mean waiting times. The corresponding queueing model under single and multiple vacation policy has also been investigated. Some numerical results have been presented in the form of tables by considering phase-type and Pareto service time distributions. The proposed analysis is based on the successive substitutions in the Markov chain equations of the queue-length distribution at an embedded post-departure epoch of a customer. We also establish relationships among the queue-length distributions at post-departure, arbitrary, and pre-arrival epochs using the classical argument based on Markov renewal theory and semi-Markov processes. Such queueing systems find applications in the performance evaluation of teletraffic part in 4G A11-IP networks.

This paper deals with a finite-buffer renewal input queueing system, where the arrivals occur in batches of random size and the server serves the customers singly. The successive service times are correlated and its representation is expressed through the continuous-time Markovian service process (C-MSP). As the buffer capacity is finite, the partial batch rejection policy and the total batch rejection policy are considered in this paper. The blocking probabilities and mean waiting time of the first, last, and an arbitrary customer of a batch are determined using the steady-state system-length distribution at pre-arrival epoch. Further, the probability of k or more consecutive customer loss (i.e., k-CCL) during a busy period is computed. The results are illustrated by some tables and graphs for different inter-batch-arrival distributions as well as different C-MSP representations.

We consider an infinite-buffer single-server queue with renewal input and Markovian service process where customers are served in batches according to a general bulk service rule. Queue-length distributions at epochs of pre-arrival, arbitrary and post-departure have been obtained along with some important performance measures such as mean queue lengths and mean waiting times in both the system as well as the queue. We also obtain the steady-state service batch size distributions as well as system-length distributions. The proposed analysis is based on roots of the associated characteristic equation of the vector-generating function of queue-length distribution at a pre-arrival epoch. Also, we provide analytical and numerical comparison between the roots method used in this paper and the matrix geometric method in terms of computational complexities and required computation time to evaluate pre-arrival epoch probabilities for both the methods. Later, we have established heavy- and light-traffic approximations as well as an approximation for the tail probabilities at pre-arrival epoch based on one root of the characteristic equation. Numerical results for some cases have been presented to show the effect of model parameters on the performance measures.

An elegant and simple solution to determine the distributions of queue length at different epochs and the waiting time for the model $$GI^{X}/M/c$$GIX/M/c is presented. In the past, the model $$GI^{X}/M/c$$GIX/M/c has been extensively analyzed using various techniques by many authors. The purpose of this paper is to present a simple and effective derivation of the analytic solution for pre-arrival epoch probabilities as a linear combination of specific geometric terms (except for the boundary probabilities when the number of servers is greater than the maximum batch size) involving the roots of the underlying characteristic equation. The solution is then leveraged to compute the waiting-time distributions of both first and arbitrary customers of an incoming batch. Numerical examples with various arrival patterns and batch size distributions are also presented. The method that is being proposed here not only gives an alternate solution to the existing methods, but it is also analytically simple, easy to implement, and computationally efficient. It is hoped that the results obtained will prove beneficial to both theoreticians and practitioners.

In this paper, we present closed-form expressions for system-length distributions in terms of roots outside the unit disk of the characteristic equation of the BMAP/R/1 queue, where arrival process is batch Markovian arrival process (BMAP) and R represents a class of distributions having rational Laplace-Stieltjes transform. The unknown boundary vector has been evaluated using the roots (inside and on the unit disk) of the characteristic equation. Several numerical results are presented for a variety of arrival and service-time distributions including phase-type (PH) and matrix-exponential (ME) which cover a wide variety of distributions that arise in applications. Using an approximated representation of ME distribution, results for BMAP/D/1 queue are also presented. We compared our result with the results obtained using classical matrix analytic method as well as cyclic reduction algorithm. It is shown that the computation-time of the proposed method does not depend upon the parameters like traffic intensity and correlation co-efficient. The method is analytically quite simple and easy to implement.

In this paper, we analyze an insurance risk model wherein the arrival of claims and their sizes occur as renewal processes. Using the duality relation in queueing theory and roots method, we derive closed-form expressions for the ultimate ruin probability, the distribution of the deficit at the time of ruin, and the expected time to ruin in terms of the roots of the characteristic equation. Finally, some numerical computations are portrayed with the help of tables.

We consider a batch arrival infinite-buffer single-server queue with generally distributed inter-batch arrival times with arrivals occurring in batches of random sizes. The service process is correlated and its structure is governed by a Markovian service process in continuous time. The proposed analysis is based on roots of the associated characteristic equation of the vector-generating function of system-length distribution at a pre-arrival epoch. We also obtain the steady-state probability distribution at an arbitrary epoch using the classical argument based on Markov renewal theory. Some important performance measures such as the average number of customers in the system and the mean sojourn time have also been obtained. Later, we have established heavy- and light-traffic approximations as well as an approximation for the tail probabilities at pre-arrival epoch based on one root of the characteristic equation. Numerical results for some cases have been presented to show the effect of model parameters on the performance measures.

This paper presents a simple closed-form analysis for evaluating system-length distributions at various epochs of the discrete-time GI/D-MSP/1 queue. The proposed analysis is based on roots of the associated characteristic equation of the vector-generating function of system-length distribution at prearrival epochs. We provide the steady-state system-length distribution at random epoch by using the classical argument based on Markov renewal theory. The queueing-time distribution has also been investigated. Numerical aspects have been tested for a variety of interarrival- and service-time distributions and a sample of numerical outputs is presented.

In this paper, we analyze airplane oil inventory problem of a base in the Republic of Korea Air Force (ROKAF) which should keep maintaining an appropriate inventory level of oil for the efficient operation of flights. In ROKAF, airplane oil supply is ordered (or delivered) at a constant time period, which means reorder point is not stochastic but deterministic. Since the airplane oil inspection time occupies large proportion of time between a reorder point and the time the oil is available for usage, it is imperative to analyze the inspection time which causes delay in fulfilling an order. In addition, if demands increase dramatically because of a war or an unexpected training, the reorder point could be shortened than in normal situations. In such abnormal circumstances, the shortened reorder point may require more delay for order fulfillment. In this setting, the inspection time endogenously determines the replenishment lead time (or supply lead time) and the pattern of the inventory. Meanwhile,...

This paper provides an analytically simple and computationally efficient solution to the discrete-time queueing model GIX /Geom/1. Using the imbedded Markov chain method, the analysis has been carried out for the late-arrival system and the results for the early-arrival system have been derived from those of the late-arrival system. The distributions of the numbers in the system at various epochs are all found in terms of roots of the underlying characteristic equation. Numerical results are also discussed.

The analysis for the B M A P/M S P/1 queueing system is based on roots of the associated characteristic equation of the vector-generating function of system-length distribution at random epoch. We obtain the steady-state system-length distributions at various epochs as well as of the actual sojourn-time distribution of an arbitrary customer in an arriving batch.

The distribution of the number of renewals for bulk arrivals in continuous time is calculated using an algorithm employed through MAPLE software. These numerical results are acquired by considering rational as well as nonrational Laplace transforms and Padé-approximated Laplace transforms for the distributions of interrenewal times. Further, through the use of Laplace transforms an elegant solution to determine the asymptotic results for the first and second moments of the number of bulk renewals is presented. These derivations help validate the numerical results and are an extension of previous work by the authors regarding single-arrival renewal theory in discrete time.

With the advent of highly integrated transmission networks, the transmission of data, such as audio, video, video streaming are transmitted over a common medium in smaller file sizes. These files have variable transmission time requirement which is of deterministic in nature. Further, the traffic generated from various sources is bursty and correlated. This particular scenario can be best modelled as a single-server queueing system with arrivals following a Markovian arrival process and service-time deterministic distribution taking one of the N possible values. For this model, we present a closed-form (in terms of roots) analysis for evaluating queueing/system-time distributions using an inversion method which is based on the roots of associated characteristic equation. Several numerical examples are presented with complete discussion.

In this paper we present closed-form expressions for the distribution of the virtual (actual) queueing time for the BMAP/R/1 and BMAP/D/1 queues, where `R' represents a class of distributions having rational Laplace‒Stieltjes transforms. The closed-form analysis is based on the roots of the underlying characteristic equation. Numerical aspects have been tested for a variety of arrival and service-time distributions and results are matched with those obtained using the matrix-analytic method (MAM). Further, a comparative study of computation time of the proposed method with the MAM has been carried out. Finally, we also present closed-form expressions for the distribution of the virtual (actual) system time. The proposed method is analytically quite simple and easy to implement.

For a class of discrete-time FIFO queueing systems with D-MAP (discrete-time Markovian arrival process), we present a distributional Little’s law that relates the distribution of the stationary number of customers in system (queue) with that of the stationary number of slots a customer spends in system (queue). Taking the multi-server D-MAP/D/c queue as an example, we demonstrate how this relation can be utilized to get the desired distribution of the number of customers. Sample numerical results are presented at the end.

A simple and elegant solution to determine the asymptotic results for the renewal density as well as for the first and second moments of the number of renewals for the discrete-time renewal process is presented. Using generating functions, the difficult-to-determine constant term in the second moment is also addressed.

The method of Laplace transforms is used to find the distribution function, mean, and variance of the number of renewals of a renewal process whose inter-arrival time distribution has a rational Laplace transform. Where the Laplace transform is not rational, we use the Pade approximation method. We apply our method to certain examples and the results are compared to those reported by other researchers.

In this paper, we present (in terms of roots) a simple closed-form analysis for evaluating system-length distribution at prearrival epochs of the GI/C-MSP/1 queue. The proposed analysis is based on roots of the associated characteristic equation of the vector-generating function of system-length distribution. We also provide the steady-state system-length distribution at an arbitrary epoch by using the classical argument based on Markov renewal theory. The sojourn-time distribution has also been investigated. The prearrival epoch probabilities have been obtained using the method of roots which is an alternative approach to the matrix-geometric method and the spectral method. Numerical aspects have been tested for a variety of arrival- and service-time distributions and a sample of numerical outputs is presented. The proposed method not only gives an alternative solution to the existing methods, but it is also analytically simple, easy to implement, and computationally efficient. It is hoped that the results obtained will prove beneficial to both theoreticians and practitioners.

In this paper, we first present (in terms of roots) a simple closed-form analysis for evaluating virtual queueing-time and actual system-time distributions for the MAP/D/1 queue. Then we obtain the system-length distribution, using the distributional Little's law. The analysis proposed here is based on the roots of the characteristic equation of the Laplace-Stieltjes transform of the virtual queueing-time distribution. Numerical aspects have been tested for a variety of arrival and service-time parameters and a sample of numerical outputs along with detailed discussion on accuracy and computation-time is presented.

In this paper, we present the steady-state system-length distributions at intermediate, outside observer’s, post-departure and pre-service completion epochs for the G I / G e o / 1 queue. It is also shown that in the limiting case, the results given in this paper tend to the continuous-time counterpart.

We consider a discrete-time multi-server finite-capacity queueing system with correlated batch arrivals and deterministic service times (of single slot), which has a variety of potential applications in slotted digital telecommunication systems and other related areas. For this queueing system, we present, based on Markov chain analysis, not only the steady-state distributions but also the transient distributions of the system length and of the system waiting time in a simple and unified manner. From these distributions, important performance measures of practical interest can be easily obtained. Numerical examples concerning the superposition of certain video traffics are presented at the end.

In this paper, we consider the numerical inversion of a variety of generating functions (GFs) that arise in the area of engineering and non-engineering fields. Three classes of GFs are taken into account in a comprehensive manner: classes of probability generating functions (PGFs) that are given in rational and non-rational forms, and a class of GFs that are not PGFs. Among others, those PGFs that are not explicitly given but contain a number of unknowns are largely considered as they are often encountered in many interesting applied problems. For the numerical inversion of GFs, we use the methods of the discrete (fast) Fourier transform and the Taylor series expansion. Through these methods, we show that it is remarkably easy to obtain the desired sequence to any given accuracy, so long as enough numerical precision is used in computations. Since high precision is readily available in current software packages and programming languages, one can now lift, with little effort, the so-called Laplacian curtain that veils the sequence of interest. To demonstrate, we take a series of representative examples: the PGF of the number of customers in the discrete-time GeoX/Geo/c queue, the same in the continuous-time MX/D/c queue, and the GFs arising in the discrete-time renewal process.

In this paper, we present (in terms of roots) a simple closed-form analysis for evaluating system-length distribution at three epochs of time (arbitrary, pre-arrival, and post-departure) and queueing-time distribution (virtual and actual) of the MAP/R/1 queue, where R represents the class of distributions whose Laplace–Stieltjes transforms are rational functions. Our analysis is based on roots of the associated characteristic equations of the (i) vector-generating function of system-length distribution and (ii) Laplace–Stieltjes transform of the virtual queueing-time distribution. The proposed method for evaluating boundary probabilities is an alternative to the matrix-analytic method as well as spectral method. Numerical aspects have been tested for a variety of arrival and service-time (including matrix-exponential (ME)) distributions and a sample of numerical outputs is presented. The method is analytically quite simple and easy to implement. It is hoped that the results obtained would prove to be beneficial to both theoreticians and practitioners.

In this article, we consider a single-server, finite-capacity queue with random bulk service rule where customers arrive according to a discrete-time Markovian arrival process (D-MAP). The model is denoted by D-MAP/G Y /1/M where server capacity (bulk size for service) is determined by a random variable Y at the starting point of services. A simple analysis of this model is given using the embedded Markov chain technique and the concept of the mean sojourn time of the phase of underlying Markov chain of D-MAP. A complete solution to the distribution of the number of customers in the D-MAP/G Y /1/M queue, some computational results, and performance measures such as the average number of customers in the queue and the loss probability are presented.

In this paper, we consider a single-server finite-capacity queue with general bulk service rule where customers arrive according to a discrete-time batch Markovian arrival process (D-BMAP). The mod...

A complete solution for the stationary queue-length distribution of a bulk-arrival, bulk-service (GIX/MY/1) queue is presented. Beginning with a known expression for the probability generating function of the stationary pre-arrival-epoch queue-length distribution, the roots method is used to invert it and determine all probabilities. Next, using level crossing arguments, theoretical relationships between pre-arrival and arbitrary-epoch probabilities are developed. These relationships are then used to directly determine a complete set of probabilities for the arbitrary-epoch queue-length distribution. Finally, selected examples are presented. These demonstrate how, given arbitrary arrival time, arrival group size and service batch size probability distributions, a complete solution for the stationary queue-length probabilities can be readily determined.

We consider a single-server queue with renewal input and Markovian service process where server serves customers in batches according to a general bulk service rule. Queue length distributions at pre-arrival and arbitrary epochs have been obtained along with some important performance measures such as probability of blocking, mean queue lengths and mean waiting times. The analysis has been carried out assuming finite-buffer space for the arriving customers. The model has potential applications in areas such as computer networks, telecommunication systems and manufacturing systems.

This paper considers a single-server queueing model with finite and infinite buffers in which customers arrive according to a discrete-time renewal process. The customers are served one at a time under discrete-time Markovian service process (D-MSP). This service process is similar to the discrete-time Markovian arrival process (D-MAP), where arrivals are replaced with service completions. Using the imbedded Markov chain technique and the matrix-geometric method, we obtain the system-length distribution at a prearrival epoch. We also provide the steady-state system-length distribution at an arbitrary epoch by using the supplementary variable technique and the classical argument based on renewal-theory. The analysis of actual-waiting-time (in the queue) distribution (measured in slots) has also been investigated. Further, we derive the coefficient of correlation of the lagged interdeparture intervals. Moreover, computational experiences with a variety of numerical results in the form of tables and graphs are discussed.

We consider a finite-buffer single-server queue with renewal input where the service is provided in batches of random size according to batch Markovian service process (BMSP). Steady-state distribution of number of customers in the system at pre-arrival and arbitrary epochs have been obtained along with some important performance measures. The model has potential applications in the areas of computer networks, telecommunication systems, and manufacturing systems, etc.

In this paper, we consider a discrete-time single-server finite-buffer batch arrival queue in which customers are served in batches according to a general bulk-service rule, that is, at least 'a' customers are needed to start a service with a maximum serving capacity of 'b' customers. The server takes a (single and multiple) vacation as soon as the queue length falls below 'a' at the completion of service. The interarrival times of batches are assumed to be independent and geometrically distributed. The service times of the batches and vacation times of the server are generally distributed and their durations are integral multiples of slot duration. We obtain queue length distributions at service completion, vacation termination, arbitrary, and prearrival epochs. Finally, we discuss various performance measures and numerical results.