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Although queueing models in the mathematical field of queueing theory are mainly studied in the steady-state regime and practical applications are interested mostly in queues in transient situations subject to burst arrivals and congestion, their use is still justified as a first step towards a more complex and thorough analysis. In these practical applications, parameters such as the traffic intensity, which is the ratio between the arrival rate and service rate, are unknown and need to be estimated statistically. In this study, a Markovian arrival and deterministic single-server queueing system, known in Kendall notation as an M ∕ D ∕ 1 queueing model, is considered. This is one of the simplest queueing models with deterministic service time and may be seen as an approximation of a variety of applications in the performance evaluation of production management, telecommunications networks, and other areas. The main goal of this manuscript is to propose a methodology to determine the sample size for an M ∕ D ∕ 1 queueing system under the Bayesian setup by observing the number of customer arrivals during the service time of a customer. To verify the efficiency and efficacy of the proposed approach, an extensive set of numerical results is presented and discussed.

A single queueing system with time-dependent exponentially distributed arrival processes and exponential machine processes (Kendall notation \begin{document}$ M_t/M_t/1 $\end{document} ) is analyzed. Modeling the time evolution for the discrete queue-length distribution by a continuous drift-diffusion process a Smoluchowski equation on the half space is derived approximating the forward Kolmogorov equations. The approximate model is analyzed and validated, showing excellent agreement for the probabilities of all queue lengths and for all queuing utilizations, including ones that are very small and some that are significantly larger than one. Having an excellent approximation for the probability of an empty queue generates an approximation of the expected outflow of the queueing system. Comparisons to several well-established approximations from the literature show significant improvements in several numerical examples.

Satellite communication is a telecommunications technique that uses satellites as a connecting component, for example VSAT. In antenna installation, there is an important process which is called the cross-polarization. Cross-polarization is one process that cannot be released inside installation of VSAT antennas for satellite communication. Sometimes, in this process, a user queue will occur. Queuing theory explain the process is done and also calculate the other factors that are in the process. By knowing queuing theory to the cross-polarization, it will be easy to know the efficiency of queuing theory in the cross-polarization. Based on the characteristics of the cross-polarization, user can be known the queuing model that used and performance of the queuing system. The queuing model for the cross-polarization, using Kendall notation, M/M/1. Based on the analysis that has been done; by using 1 server the value of service level (ρ) is 0.67, using 2 servers = 0.33 and 3 servers = 0.22. The waiting time in the queue is longer if using 1 server which is 0.67 hours or 40 minutes. If a satellite operator uses 2 servers, waiting time in the queue is 25 minutes and 3 servers is 2.8 minutes which means that there is almost no waiting time in the queue.

Queues with general inter-arrival times in batches of random sizes, multi-servers, and finite-buffer spaces are studied, as the determination of their performance measures is a challenging inferential problem. This study focuses on estimating the important performance measures of GIX/M/c/N queues under finite samples. In Kendall notation, this abbreviation represents independent general (GI) distributed inter-arrival times for bulk arrivals of size X, Markovian (M) service times, c identical servers working in parallel, and a maximum number of N users simultaneously allowed in the system, including those under service. Kernel-based methods (constituting a class of well-known nonparametric methods) and classical methods are used to adjust the arrival and service processes. Extensive simulations are performed to verify the quality of the estimations for samples sizes of approximately 500 to provide estimates with a relative error of less than 10%. We also relate notable new insights, for example, that simpler models, such as finite Markovian multi-server queues, M/M/c/N in Kendal notation, are in certain cases sufficiently robust and precise to satisfactorily solve the problem of performance measure determination. The limitations of the results are discussed, and notable topics to be further developed in this research area are presented.

In many everyday situations in which a queue is formed, queueing models may play a key role. By using such models, which are idealizations of reality, accurate performance measures can be determined, such as traffic intensity (ρ), which is defined as the ratio between the arrival rate and the service rate. An intermediate step in the process includes the statistical estimation of the parameters of the proper model. In this study, we are interested in investigating the finite-sample behavior of some well-known methods for the estimation of ρ for single-server finite Markovian queues or, in Kendall notation, M/M/1/K queues, namely, the maximum likelihood estimator, Bayesian methods, and bootstrap corrections. We performed extensive simulations to verify the quality of the estimators for samples up to 200. The computational results show that accurate estimates in terms of the lowest mean squared errors can be obtained for a broad range of values in the parametric space by using the Jeffreys’ prior. A numerical example is analyzed in detail, the limitations of the results are discussed, and notable topics to be further developed in this research area are presented.

Queueing applications are often complicated by dependence among interarrival times and service times. Such dependence is common in networks of queues, where arrivals are departures from other queues or superpositions of such complicated processes, especially when there are multiple customer classes with class-dependent service-time distributions. We show that the robust queueing approach for single-server queues proposed in the literature can be extended to yield improved steady-state performance approximations in the standard stochastic setting that includes dependence among interarrival times and service times. We propose a new functional robust queueing formulation for the steady-state workload that is exact for the steady-state mean in the M/GI/1 model and is asymptotically correct in both heavy traffic and light traffic. Simulation experiments show that it is effective more generally. The online appendix is available at https://doi.org/10.1287/opre.2017.1649 .

A certain type of queueing system that is quite common in manufacturing systems occurs when the time between the arrivals of items approximately follows an exponential distribution with rate λ , the services are mechanized and their times may be considered approximately constant ( b ). In Kendall notation, such a queueing system is well known as an M ∕ D ∕ 1 queue; despite being one of the simplest queueing models, it has wide applicability to numerous practical situations as a first approximation by a steady-state model before a deeper analysis can be performed by means of more sophisticated transient-regime stochastic models that consider, for example, burst arrival, block arrivals, congestion, and so on. In queues, one very important parameter that must estimated is the traffic intensity, defined for an M ∕ D ∕ 1 queue as ρ = λ b . This article aims to investigate statistical methods to estimate ρ , namely, the maximum likelihood and Bayes estimators, by considering the number of customers present in the system at successive departure epochs, which is a very natural way to collect data. An extensive set of computational results from Monte Carlo simulations is shown to establish the efficiency and effectiveness of the proposed approaches, which will possibly enhance practical applications.

This paper is concerned with an M/PH/K queue with customer abandonment, constant impatient time, and many servers. By combining the method developed in Choi et al. (Math Oper Res 29:309–325, 2004) and Kim and Kim (Perform Eval 83–84:1–15, 2015) and the state space reduction method introduced in Ramaswami (Stoch Models 1:393–417, 1985), the paper develops an efficient algorithm for computing performance measures for the queueing system of interest. The paper shows a number of properties associated with matrices used in the development of the algorithm, which make it possible for the algorithm, under certain conditions, to handle systems with up to one hundred servers. The paper also obtains analytical properties of performance measures that are useful in gaining insight into the queueing system of interest.

In queuing theory, a major interest of researchers is studying the behavior and formation process and analyzing the performance characteristics of queues, particularly the traffic intensity, which is defined as the ratio between the arrival rate and the service rate. How these parameters can be estimated using some statistical inferential method is the mathematical problem treated here. This article aims to obtain better Bayesian estimates for the traffic intensity of M/M/1 queues, which, in Kendall notation, stand for Markovian single-server infinity queues. The Jeffreys prior is proposed to obtain the posterior and predictive distributions of some parameters of interest. Samples are obtained through simulation and some performance characteristics are analyzed. It is observed from the Bayes factor that Jeffreys prior is competitive, among informative and non-informative prior distributions, and presents the best performance in many of the cases tested.

The paper considers retrial queueing system M /M /1/ 0 with combined service discipline, namely, a customer from the orbit is serviced in its turn, but in case of a free channel an arrival from the original flow is serviced immediately. The author obtains the expressions for state probabilities as well as ergodicity conditions. The system is compared with the Lakatos-type system.

An M / M / C queueing system operating in a Markovian environment is studied. This paper focuses on the stationary behavior and presents the theoretical framework. For a special case, analytical results are derived that are analogous to the classical solutions for the simple M / M / C queue. The elaborate analysis of a specific case is given to illustrate the basic idea of the framework. A technical proof with respect to the existence of d − 1 roots is displayed to sustain the corresponding theory.

This paper focuses on status age, which is a metric for measuring the freshness of a continually updated piece of information (i.e., status) as observed at a remote monitor. In paper, we study a system in which a sensor sends random status updates over a dynamic network to a monitor. For this system, we consider the impact of having messages take different routes through the network on the status age. First, we consider a network with plentiful resources (i.e., many nodes that can provide numerous alternate paths), so that packets need not wait in queues at each node in a multihop path. This system is modeled as a single queue with an infinite number of servers, specifically as an $M/M/\infty $ queue. Packets routed over a dynamic network may arrive at the monitor out of order, which we account for in our analysis for the $M/M/\infty $ model. We then consider a network with somewhat limited resources, so that packets can arrive out of order but also must wait in a queue. This is modeled as a single queue with two servers, specifically an $M/M/2$ queue. We present the exact approach to computing the analytical status age, and we provide an approximation that is shown to be close to the simulated age. We also compare both models with $M/M/1$ , which corresponds to severely limited network resources, and we demonstrate the tradeoff between the status age and the unnecessary network resource consumption.

This research aims to determine the queue model on a motorcycle parking area at Jember Universityand its performance measures. The data collection method in this research uses the observation method. Data taken are the number of arrivals, the number of departures, and service time. To get arrival distribution and service time distribution use mathematical calculation and Kolmogorov-Smirnov Test with SPSS Statistics. After arrival distribution and service time distribution are known, then using Kendall Notation rule to get queue model. Formula derivation and POM-QM for Windows are used to obtain performance measurement values in the queue model. After getting the data needed through observation, then analysedtaht data to determine the value of arrival rate and service rate, then the data is reanalysed to find out the data obtained has been steady-state. This research is known that steady-state, so that distribution test can be done, with the result that the arrival distribution was Poisson distribution and the service time distribution was Exponential distribution. In modelling the queue Kendall Notation is required. It’s used to clarify how the queue system reviewed works and is modelled. Based on the results of data analysis in this research, the queue model obtained was (M/M/1):(FIFO/∞/∞).

A typical application of the statistical models can be found in queuing systems to model the waiting experiences. This statistical modeling of the waiting is well known as queuing theory. This chapter is devoted to study the queuing theory in the context of computer and communication networks. In this chapter, the author will first introduce the basic concept of queuing theory in Section 15.1. The application of queuing theory in the form of queuing systems for computer and communication networks will be presented in Section 15.2. As a background of the queuing system, the Poisson point process will be then reviewed in Section 15.3. Various performance measures and their relationship with Little's law will be discussed in Section 15.4. This chapter will be closed by introducing Kendall's notation for specifying queuing systems in Section 15.5.

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.

We consider a state-dependent $$M_{n}$$Mn/$$G_{n}$$Gn/1 queueing system with both finite and infinite buffer sizes. We allow the arrival rate of customers to depend on the number of people in the system. Service times are also state dependent and service rates can be modified at both arrivals and departures of customers. We show that the steady-state solution of this system at arbitrary times can be derived using the supplementary variable method, and that the system's state at arrival epochs can be analyzed using an embedded Markov chain. For the system with infinite buffer size, we first obtain an expression for the steady-state distribution of the number of customers in the system at both arbitrary and arrival times. Then, we derive the average service time of a customer observed at both arbitrary times and arrival epochs. We show that our state-dependent queueing system is equivalent to a Markovian birth-and-death process. This equivalency demonstrates our main insight that the $$M_{n}$$Mn/$$G_{n}$$Gn/1 system can be decomposed at any given state as a Markovian queue. Thus, many of the existing results for systems modeled as an M / M / 1 queue can be carried through to the much more practical M / G / 1 model with state-dependent arrival and service rates. Then, we extend the results to the $$M_{n}$$Mn/$$G_{n}$$Gn/1 queueing systems with finite buffer size.

In this paper we consider the MMAP/PH/1 priority queue, both the case of preemptive resume and the case of non-preemptive service. The main idea of the presented analysis procedure is that the sojourn time of the low priority jobs in the preemptive case (and the waiting time distribution in the non-preemptive case) can be represented by the duration of the busy period of a special Markovian fluid model. By making use of the recent results on the busy period analysis of Markovian fluid models it is possible to calculate several queueing performance measures in an efficient way including the sojourn time distribution (both in the time domain and in the Laplace transform domain), the moments of the sojourn time, the generating function of the queue length, the queue length moments and the queue length probabilities.

A queueing system with 2 parallel workstations is common in the field. Typically, the workstations have different features in terms of the inter arrival times of customers and the service times for the customers. Computer simulation study on the optimal server allocation for parallel heterogeneous queueing systems with fixed number of identical servers is presented in this paper. The queueing system is optimized with respect to minimizing the weighted system time of the customers served by 2 parallel workstations. The system time formula for the M/M/c systems in Kendall’s notation is known. Thus, we first compute the optimal allocation for parallel M/M/c systems, comparing the results with those from the computer simulation experiments, and have the same results. The CETI rule is devised through optimizing M/M/c cases, which allocates the servers based on Close or Equal Traffic Intensities between workstations. Traffic intensity is defined as the arrival rate divided by the service rate times the number of servers. The CETI rule is shown to work for M/G/c, G/M/c queueing systems by numerous computer simulation experiments, even if the rule cannot be proven analytically. However, the CETI rule is shown not to work for some of G/G/c systems.

By studying the spectral properties of the underlying operator corresponding to the M / G / 1 queueing model with second optional service, we obtain that the time-dependent solution of the model strongly converges to its steady-state solution. We also show that the time-dependent queueing size at the departure point converges to the corresponding steady-state queueing size at the departure point.

A Markovian single-server queueing model with Poisson arrivals and state-dependent service rates, characterized by a logarithmic steady-state distribution, is considered. The Laplace transforms of the transition probabilities and of the densities of the first-passage time to zero are explicitly evaluated. The performance measures are compared with those ones of the well-known M / M / 1 queueing system. Finally, the effect of catastrophes is introduced in the model and the steady-state distribution, the asymptotic moments and the first-visit time density to zero state are determined.

This article discusses the steady state analysis of the M / G / 2 queuing system with two heterogeneous servers under new queue disciplines when the classical First Come First Served ‘(FCFS)’ queue discipline is to be violated. Customers are served either by server-I according to an exponential service time distribution with mean rate μ or by server-II with a general service time distribution B ( t ) . Sequel to some objections raised in the literature on the use of the classical FCFS queue discipline in heterogeneous service systems, two alternative queue disciplines (Serial and Parallel) are considered in this work with the objective that if the FCFS is violated then the violation is a minimum in the long run. Using the embedded method under the serial queue discipline and the supplementary variable technique under the parallel queue discipline, we present an exact analysis of the steady state number of customers in the system and most importantly, the actual waiting time expectation of customers in the system. Our work shows that one can obtain all stationary probabilities and other vital measures for this queue under certain simple but realistic assumptions.

Closed, finite queueing networks are applicable to many different manufacturing and service system settings. The incorporation of material handling and transportation networks in finite buffer closed queueing networks is studied. A novel queue decomposition approach using state dependent queues to capture the buffer of finite M/M/1/K queues is shown to be a viable approach for modelling these systems. Each M / M / 1 / K queue is replaced with a coupled state dependent queue plus an M/M/1 queue. An extended mean value analysis (MVA) algorithm is employed to demonstrate the integration of the state dependent queues for the buffers in the approach. Under certain restrictions concerning the network population, finite queueing networks with the state dependent queues acting as buffers should have a product form distribution. This paper focuses on M/M/1/K queues and their transformation while future papers will treat the multi-server case. Several different closed series (i.e. cyclic), merge, and split topological systems of finite queues are analyzed and presented.

Part 1: Network Analysis and Dimensioning; International audience; In this paper, we consider single server queueing system with a finite buffer, MAP input and independent generally distributed service times. Customers are selected for the service in accordance with the LIFO (Last In – First Out) service discipline. It is well known that stationary distribution of the number of customers in such a system coincides with the corresponding distribution in the system with FIFO (First In – First Out) discipline which has been studied in the literature early. In the present research we focus on investigating the stationary distribution of waiting (sojourn) time in the system.

By studying the spectral properties of the underlying operator corresponding to the M/G/1 queueing model with optional second service we obtain that the time-dependent solution of the model strongly converges to its steady-state solution. We also show that the time-dependent queueing size at the departure point converges to the corresponding steady-state queueing size at the departure point.

The object of this research in the queueing theory is a theorem about the Strong-Law-of-Large-Numbers (SLLN) under the conditions of heavy traffic in a multiserver open queueing network. SLLN is known as a fluid limit or fluid approximation. In this work, we prove that the long-term average rate of growth of the queue length process of a multiserver open queueing network under heavy traffic strongly converges to a particular vector of rates. SLLN is proved for the values of an important probabilistic characteristic of the multiserver open queueing network investigated as well as the queue length of jobs.

An efficient numerical evaluation technique is presented for families of finite Markov chains indexed by a parameter e, that possess a monotonicity property for the chain at e = 0. The monotonicity allows for retrieving the series expansion of the steady state solution in e = 0 in O( NM ) operations, where N is the size of the state space and M is the number of terms in the series expansion. We then apply the method to a layered queueing network with four queues, three queues in tandem and one queue for the servers operating this tandem queue.

This article presents a paradigm where no stochastic assumptions are made on a queue’s arrival process. To this end, we study two queueing systems which exhibit a form of stability under an arbitrary arrival process. The first queueing system applies Blackwell’s Approachability Theorem and the second analyzes the Vacuum Cleaner Problem.

The present study deal with the development of statistical methodology for updating the basic arrival and service time distributions in respect of prior variations. These updated arrival and services time distributions provide us the modified form of traffic intensity as the ratio of updated mean service time to updated mean inter-arrival time. As such all the basic queue characteristics will be developed in the changed scenario.

In this paper we present an exact steady-state analysis of a discrete-time Geo/G/1 queueing system with working vacations, where the server can keep on working, but at a slower speed during the vacation period. The transition probability matrix describing this queuing model can be seen as an M/G/1-type matrix form. This allows us to derive the probability generating function (PGF) of the stationary queue length at the departure epochs by the M/G/1-type matrix analytic approach. To understand the stationary queue length better, by applying the stochastic decomposition theory of the standard M/G/1 queue with general vacations, another equivalent expression for the PGF is derived. We also show the different cases of the customer waiting to obtain the PGF of the waiting time, and the normal busy period and busy cycle analysis is provided. Finally, we discuss various performance measures and numerical results, and an application to network scheduling in the wavelength division-multiplexed (WDM) system illustrates the benefit of this model in real problems.

We consider a 2-class, single-server, preemptive priority queueing model in which the high-priority customers form a classical M/M/1 queue, while the low-priority customers form the so-called Israeli Queue with at most N different groups and unlimited-size batch service. We provide an extensive probabilistic analysis and calculate key performance measures. Special cases are analyzed and numerical examples are presented and discussed.

In Sigman (J. Appl. Probab. 48A:209–216, 2011b), a first exact simulation algorithm was presented for the stationary distribution of customer delay for FIFO M/G/c queues in which ρ=λ/μ

The paper is devoted to the analysis of queueing systems in the context of the network and communication theory. We investigate a theorem on the law of the iterated logarithm for a queue of jobs in a multiserver open queueing network under heavy traffic conditions.

We consider a non-cooperative queueing environment where a finite number of customers independently choose when to arrive at a queueing system that opens at a given point in time and serves customers on a last-come first-serve preemptive-resume (LCFS-PR) basis. Each customer has a service time requirement which is identically and independently distributed according to some general probability distribution, and they want to complete service as early as possible while minimizing the time spent in the queue. In this setting, we establish the existence of an arrival time strategy that constitutes a symmetric (mixed) Nash equilibrium, and show that there is at most one symmetric equilibrium. We provide a numerical method to compute this equilibrium and demonstrate by a numerical example that the social efficiency can be lower than the efficiency induced by a similar queueing system that serves customers on a first-come first-serve (FCFS) basis.

This paper considers two randomized control policies. One is (p, F)-policy queue which deals with the issue of randomized controlling arrivals to a queueing system and the server requires a start-up time before allowing customers to enter the system. Another is (q, N)-policy queue which considers the common issue of controlling service in a queueing system randomly, and the server requires a start-up time before providing service. The steady-state probability distribution of the system size and system performances measures are developed for both queues. In addition, we uncover an interrelationship between the (p, F)- and (q, N)-policy M/M/1/K queues by a series of propositions. The advantage created through interrelationship is that the solution of one queue has been derived, which assists us in obtaining that of the other queue easily. Finally, numerical results are presented for illustration purposes.

This paper considers the M/M/Nrepairable queuing system. The customers' arrival is a Poisson process. The servers are subject to breakdown according to Poisson processes with different rates in idle time and busy time, respectively. The breakdown servers are repaired by repairmen, and the repair time is an exponential distribution. Using probability generating function and transform method, we obtain the steady-state probabilities of the system states, the steady-state availability of the servers, and the mean queueing length of the model.

Queueing theory is the study of prediction and evaluation of the system performance. It has been studied and used since long time. It mainly studies the waiting line or queues. A queueing system can be described as customers arriving for service, waiting for service if it is not immediate, and if having waited for service, leaving the system after being served. Queueing theory was developed to provide models to predict the behavior of systems that attempt to provide service for such randomly arising demands. Different queueing models are proposed to measure the system performance. These models differentiate with each other according to the Kendall's notation indicating the arrivals, service, servers, system capacity and the queue discipline. The purpose of our study is to design a discrete event simulation for a commonly used Queueing Model M/D/l. The model represents exponential arrival of customers with a deterministic service rate on a single server system, for example a production company with a single server machine or an output buffer of an ATM multiplexer where packets arrive exponentially and serviced as deterministically. The case study of the output buffer of an ATM multiplexer is included to compare the simulation results with analytical findings of the Model. We have designed the simulation using C/C++ programming language.

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.

A method of the analysis of a queueing system with the processor-sharing discipline is briefly described. In addition, recurrent formulas applied to calculate the moments of the distribution of the random variable describing a call’s sojourn time of length u.

This paper considers an M/M/r queueing system with infinite capacity, in which the number of working servers changes depending on the queue length. The steady-state probability distributions and the expected number of customers in the system are derived, which are used to construct a cost function. In order to minimize the expected cost of the system, we use the genetic algorithm to find the best thresholds of queue length in activating servers and their corresponding service rate. Some illustrative examples are provided to demonstrate how the process of this algorithm works for the optimal management policy of the multi-server queueing system.

Finite buffer, single-server queueing systems and networks are difficult to analyze since the length of time a customer spends in the system does not follow the Markovian property. A two-moment approximation schema is developed for the probability distribution of M/G/1/K systems and extended to the analysis of M/G/1/K queueing networks. The general purpose of this paper is to develop a flexible and practical transform-free approach for computing the probability distribution and performance measures of the system as well as identify the underlying properties of these systems. It is shown that for most performance measures, a sigmoid or S-shaped curve with an inflection point at @r=1 appears as K->~. This has direct implications for the analysis and optimization of such systems. The performance modelling of the M/G/1/K queueing networks of general topologies along with extensive numerical results accompany the paper along with the linear concave performance measures for these systems.

We consider an infinite-buffer single-server queue with renewal input. The service to the queueing system is provided in batches of random size, according to a batch Markovian service process (BMSP). The queue length distribution of the number of customers in the system at pre-arrival and arbitrary epochs has been obtained along with some important performance measures, such as the mean number of customers in the system and the mean system sojourn time of a customer. Secondly, we study a similar queueing system with queue-length-dependent inter-arrival times and obtain the above-mentioned state probabilities and performance measures. These queueing models have potential applications in the areas of computer networks, telecommunication systems, manufacturing systems, etc.

Waiting line is formed whenever the service rate is lower than the demand for the service. At many fuel stations there is always a queue to get the fuel due to which it may happen that some of the customers may move to competitor's retail outlet where the waiting time in queue is less. Formation of queue causes the increased waiting time for the customers, over-utilisation of the servers and loss of customer good will. Application of queuing theory determines the measure of the performance of the service facility and which in turn helps to design appropriate/optimised service facility. In this paper, a single channel multiple server model is used to analyse the characteristics of queuing model.

We consider the queueing maximal covering location-allocation problem (QM-CLAP) with an M/G/1 queueing system. We first formulate the problem as a binary quadratic programming problem and then propose a new solution procedure based on decomposition of the problem into smaller binary quadratic sub-problems. The heuristic procedure GRASP is used to solve the sub-problems, as well as the entire model. Some computational results are also presented.

This paper focuses on new measures of performance in single-server Markovian queueing system. These measures depend on the moments of order statistics. The expected value and the variance of the maximum (minimum) number of customers in the system as well as the expected value and the variance of the minimum (maximum) waiting time are presented. Application to an M/M/1 model is given to illustrate the idea and the applicability of the proposed measures.

This paper presents an approximating model for a 2-class weighted fair queueing (or random polling) model. The approximating system can be analyzed analytically to obtain mean performance measures such as expected delay. We show through a formal argument that the approximation works well when the overall utilization of the system @r is small. Based on simulation experiments, we develop a modified version of the approximation that is accurate for a wide range of @r. Finally, we extend the approximation to more complex queueing scenarios, such as the low-latency-queueing discipline and systems with more than 2 classes.

The article deals with the queueing system of GI/G/1 type with individual service and batch arrival of customers. The method of integral equations on a half-axis [0, ∞) is applied to obtain new results for the actual waiting time w n of nth arriving customer. The transient and steady state as n tends to infinity are considered. Some simplifications and numerical results for M/M/1, M/E 2/1, and M 2/M/1 queueing systems are derived as well.