On priority queues with impatient customers

In this paper, we study three different problems where one class of customers is given priority over the other class. In the first problem, a single server receives two classes of customers with general service time requirements and follows a preemptive-resume policy between them. Both classes are impatient and abandon the system if their wait time is longer than their exponentially distributed patience limits. In the second model, the low-priority class is assumed to be patient and the single server chooses the next customer to serve according to a non-preemptive priority policy in favor of the impatient customers. The third problem involves a multi-server system that can be used to analyze a call center offering a call-back option to its impatient customers. Here, customers requesting to be called back are considered to be the low-priority class. We obtain the steady-state performance measures of each class in the first two problems and those of the high-priority class in the third problem by exploiting the level crossing method. We furthermore adapt an algorithm from the literature to obtain the factorial moments of the low-priority queue length of the multi-server system exactly.      

Analysis of nonpreemptive priority queues with multiple servers and two priority classes

In this paper, we model a priority multiserver queueing system with two priority classes. A high priority customer has nonpreemptive priority over low priority customers. The approaches for solving the problem are the state-reduction based variant of Kao, the modified boundary algorithm of Latouche, the logarithmic reduction algorithm of Latouche and Ramaswami, and the power-series method of Blanc. The objectives of this paper are to present a power-series implementation for the priority queue and to evaluate the relative efficiencies of alternative procedures to compute various performance characteristics. In the paper, we find that at times the logarithmic reduction algorithm may not perform as well as expected and the power-series approach can occasionally pose numerical difficulties.     

Benchmark policies for utility-carrying queues with impatience

Queueing Systems - Men and jobs alike are characterized by a single trait, which may take on categorical values according to given population frequencies. Men arrive to the system following a...     

Two fluid approximations for multi-server queues with abandonments

Insight is provided into a previously developed M/M/s/r+M(n) approximation for the M/GI/s/r+GI queueing model by establishing fluid and diffusion limits for the approximating model. Fluid approximations for the two models are compared in the many-server efficiency-driven (overloaded) regime. The two fluid approximations do not coincide, but they are close.     

Analysis of multi-server queues with station and server vacations

In this paper, we consider GI/M/c queues with two classes of vacation mechanisms: Station vacation and server vacation. In the first one, all the servers take vacation simultaneously whenever the system becomes empty, and they also return to the system at the same time, i.e., station vacation is a group vacation for all servers. This phenomenon occurs in practice, for example, when the system consists of a set of machines monitored by a single operator, or the system consists of inseparable interconnected parallel machines. In such situations the whole station has to be treated as a single entity for vacation when the system is utilized for a secondary task. For the second class of vacation mechanisms, each server takes its own vacation whenever it complexes a service and finds no customers waiting in the queue, which occurs, for instance in the post office, when each server is a relatively independent working unit, and can itself be used for other purposes. For both models, we derive steady state probabilities that have matrix geometric form, and develop computational algorithms to obtain numerical solutions. We also analyze and make comparisons of these models based on numerical observations.     

Ordered priority queues

A new data structure called ordered priority queue is introduced in this paper. Elements stored in the data structure have a primary order (key) and a secondary order (priority) associated with them. An ordered min-priority queue allows users to find the minimum priority element in any range (according to key order) inO(logn) time. Such a data structure withn elements can be created inO(n logn) time usingO(n) storage. A specific implementation based on median split trees is presented. Sequential access of the elements can be done inO(n log logn) time andO(logn) extra storage.This work was supported in part by NASA under grant NAG 5-739.     

Approximations for multi-server queues: System interpolations

This paper provides a unifying method of generating and/or evaluating approximations for the principal congestion measures in aGI/G/s queueing system. The main focus is on the mean waiting time, but approximations are also developed for the queue-length distribution, the waiting-time distribution and the delay probability for the Poisson arrival case. The approximations have closed forms that combine analytical solutions of simpler systems, and hence they are referred to as system-interpolation approximations or, simply, system interpolations. The method in this paper is consistent with and generalizes system interpolations previously presented for the mean waiting time in theGI/G/s queue.     

Gaussian skewness approximation for dynamic rate multi-server queues with abandonment

The multi-server queue with non-homogeneous Poisson arrivals and customer abandonment is a fundamental dynamic rate queueing model for large scale service systems such as call centers and hospitals. Scaling the arrival rates and number of servers arises naturally when a manager updates a staffing schedule in response to a forecast of increased customer demand. Mathematically, this type of scaling ultimately gives us the fluid and diffusion limits as found in Mandelbaum et al., Queueing Syst 30:149–201 (1998) for Markovian service networks. The asymptotics used here reduce to the Halfin and Whitt, Oper Res 29:567–588 (1981) scaling for multi-server queues. The diffusion limit suggests a Gaussian approximation to the stochastic behavior of this queueing process. The mean and variance are easily computed from a two-dimensional dynamical system for the fluid and diffusion limiting processes. Recent work by Ko and Gautam, INFORMS J Comput, to appear (2012) found that a modified version of these differential equations yield better Gaussian estimates of the original queueing system distribution. In this paper, we introduce a new three-dimensional dynamical system that is based on estimating the mean, variance, and third cumulant moment. This improves on the previous approaches by fitting the distribution from a quadratic function of a Gaussian random variable.     

Analysis of customers’ impatience in queues with server vacations

Many models for customers impatience in queueing systems have been studied in the past; the source of impatience has always been taken to be either a long wait already experienced at a queue, or a long wait anticipated by a customer upon arrival. In this paper we consider systems with servers vacations where customers’ impatience is due to an absentee of servers upon arrival. Such a model, representing frequent behavior by waiting customers in service systems, has never been treated before in the literature. We present a comprehensive analysis of the single-server, M/M/1 and M/G/1 queues, as well as of the multi-server M/M/c queue, for both the multiple and the single-vacation cases, and obtain various closed-form results. In particular, we show that the proportion of customer abandonments under the single-vacation regime is smaller than that under the multiple-vacation discipline. This work was supported by the Euro-Ngi network of excellence.     

Two competing discrete-time queues with priority

This paper considers a class of two discrete-time queues with infinite buffers that compete for a single server. Tasks requiring a deterministic amount of service time, arrive randomly to the queues and have to be served by the server. One of the queues has priority over the other in the sense that it always attempts to get the server, while the other queue attempts only randomly according to a rule that depends on how long the task at the head of the queue has been waiting in that position. The class considered is characterized by the fact that if both queues compete and attempt to get the server simultaneously, then they both fail and the server remains idle for a deterministic amount of time. For this class we derive the steady-state joint generating function of the state probabilities. The queueing system considered exhibits interesting behavior, as we demonstrate by an example.     

Algorithmic methods for multi-server queues with group arrivals and exponential services

We discuss algorithms for the computation of the steady-state features of the c-server queue with exponential service times and bounded group arrivals. While our methods are valid for general interarrival time distributions, we treat in detail the simplifications obtained by using a distribution of phase type. Oueue length densities at times prior to arrivals and at arbitrary times are obtained in a modified matrix-geometric form. Their means and variances are found in computationally tractable forms. We also present algorithmic methods for the waiting time and the virtual waiting time distributions of a customer in a group and obtain the means and variances of these distributions in tractable forms. Numerical examples show that the effects of changing various parameters of the queuing model may so be examined at a small computational cost.     

System with priority queues and unreliable server

A single server queueing system with an unreliable server and priority customers is considered. The limit distribution of the number of ordinary customers in the system is obtained.     

Numerical analysis of multi-server queues with deterministic service and special phase-type arrivals

In this paper we study multi-server queues with deterministic service times and a phase-type arrival process. In particular, we consider for the interarrival time hyperexponential distributions and mixtures of Erlang distributions with the same scale parameter. We give an algorithm to compute the steady state probabilities of the number of customers in the system and derive explicit expressions for various operating characteristics.Special attention is paid to the numerical evaluation of the required transition probabilities and the implementation of the iterative solution method for the steady state probabilities.

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Zusammenfassung In dieser Arbeit werden Bedienungssysteme mit mehreren parallelen Schaltern studiert, wobei ein Ankunftsstrom vom Phasentyp und deterministische Bedienungszeiten angenommen werden. Speziell werden hyperexponentialverteilte Zwischenankunftszeiten betrachtet oder solche, die nach einer Mischung von Erlangverteilungen mit dem selben Skalenparameter verteilt sind. Es werden ein Algorithmus zur Berechnung der stationären Wahrscheinlichkeiten für die Anzahl der Kunden im System angegeben sowie explizite Ausdrücke für diverse Charakteristiken hergeleitet.Besonderes Gewicht liegt auf der numerischen Berechnung der benötigten Übergangswahrscheinlichkeiten und der Implementierung der iterativen Methode zur Berechnung der stationären Wahrscheinlichkeiten.

     

Optimal priority queues: The simple discretionary priority rule

Summary The simple discretionary priority rule defines a point of discretion for every customer class up to which preemption by newly arriving customers of higher classes is possible. The paper derives the transient state results for the case with arbitrary numbers of customer classes and general service time distributions. The optimal point of discretion is determined for cost functions linear in the expected number of customers of each class present in the system.

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Zusammenfassung Die einfache diskretionäre Prioritätsregel legt für jede Kundenklasse einen Punkt der Diskretion fest, bis zu welchem Verdrängung durch neuankommende Kunden höherer Klassen möglich ist. Ergebnisse für das zeitabhängige Verhalten von Prozessen mit beliebiger Anzahl von Kundenklassen und allgemeinverteilten Bedienzeiten werden abgeleitet. Der optimale Punkt der Diskretion wird bestimmt für eine Kostenfunktion linear im Erwartungswert der Anzahl der im System anwesenden Kunden einer jeden Klasse.

     

Analysis of preemptive loss priority queues with preemption distance

In a queueing system with preemptive loss priority discipline, customers disappear from the system immediately when their service is preempted by the arrival of another customer with higher priority. Such a system can model a case in which old requests of low priority are not worthy of deferred service. This paper is concerned with preemptive loss priority queues in which customers of each priority class arrive in a Poisson process and have general service time distribution. The strict preemption in the existing model is extended by allowing the preemption distance parameterd such that arriving customers of only class 1 throughp — d can preempt the service of a customer of classp. We obtain closed-form expressions for the mean waiting time, sojourn time, and queue size from their distributions for each class, together with numerical examples. We also consider similar systems with server vacations.     

Transforming binary sequences using priority queues

A priority queue transforms an input sequence into an output sequence which is a re-ordering of the sequence . The setR of all such related pairs is studied in the case that is a binary sequence. It is proved thatR is a partial order and that ¦R¦=c _n+1, the (n+1)th Catalan number. An efficient (O(n ²)) algorithm is given for computing the number of outputs achievable from a given input.     

Optimal arrival rate and service rate control of multi-server queues

We consider the problem of optimal control of a multi-server queue with controllable arrival and service rates. This study is motivated by its potential application to the design and control of data centers. The cost structure includes customer holding cost which is a non-decreasing convex function of the number of customers in the system, server operating cost which is a non-decreasing convex function of the chosen service rate, and system operating reward which is a non-decreasing concave function of the chosen arrival rate. We formulate the problem as a continuous-time Markov decision process and derive structural properties of the optimal control policies under both discounted cost and average cost criterions.