Fluid models of many-server queues with abandonment

We study many-server queues with abandonment in which customers have general service and patience time distributions. The dynamics of the system are modeled using measure-valued processes, to keep track of the residual service and patience times of each customer. Deterministic fluid models are established to provide a first-order approximation for this model. The fluid model solution, which is proved to uniquely exist, serves as the fluid limit of the many-server queue, as the number of servers becomes large. Based on the fluid model solution, first-order approximations for various performance quantities are proposed.     

A note on a limit interchange for many-server queues

A connection between open and closed many-server queueing systems is examined. Two limits are considered: (i) the number and reliability of machines (customers) increase simultaneously while the offered load remains constant (Poisson limit), and (ii) the number of machines (customers) and repairmen (servers) increase while the utilization remains close to unity (QED limit). It is argued that the two limits are interchangeable.     

Convergence to equilibrium states for fluid models of many-server queues with abandonment

Fluid models, in particular their equilibrium states, have become an important tool for the study of many-server queues with general service and patience time distributions. However, it remains an open question whether the solution to a fluid model converges to the equilibrium state and under what condition. We show in this paper that the convergence holds under some conditions. Our method builds on the framework of measure-valued processes, which keeps track of the remaining patience and service times.     

Fluid limits of many-server queues with abandonments,general service and continuous patience time distributions

This paper extends the works of Kang and Ramanan (2010) and Kaspi and Ramanan (2011), removing the hypothesis of absolute continuity of the service requirement and patience time distributions. We consider a many-server queueing system in which customers enter service in the order of arrival in a non-idling manner and where reneging is considerate. Similarly to Kang and Ramanan (2010), the dynamics of the system are represented in terms of a process that describes the total number of customers in the system as well as two measure-valued processes that record the age in service of each of the customers being served and the “potential” waiting times. When the number of servers goes to infinity, fluid limit is established for this triple of processes. The convergence is in the sense of probability and the limit is characterized by an integral equation.     

Validity of heavy-traffic steady-state approximations in many-server queues with abandonment

We consider \(GI/Ph/n+M\) parallel-server systems with a renewal arrival process, a phase-type service time distribution, \(n\) homogenous servers, and an exponential patience time distribution with positive rate. We show that in the Halfin–Whitt regime, the sequence of stationary distributions corresponding to the normalized state processes is tight. As a consequence, we establish an interchange of heavy-traffic and steady-state limits for \(GI/Ph/n+M\) queues.     

Bayesian inference in Markovian queues

This paper is concerned with the Bayesian analysis of general queues with Poisson input and exponential service times. Joint posterior distribution of the arrival rate and the individual service rate is obtained from a sample consisting inn observations of the interarrival process andm complete service times. Posterior distribution of traffic intensity inM/M/c is also obtained and the statistical analysis of the ergodic condition from a decision point of view is discussed.     

Exponential bounds for queues with Markovian arrivals

Exponential bounds [queueb]e ^b are found for queues whose increments are described by Markov Additive Processes. This is done by application of maximal inequalities to exponential martingales for such processes. Through a thermodynamic approach the constant is shown to be the decay rate for an asymptotic lower bound for the queue length distribution. The class of arrival processes considered includes a wide variety of Markovian multiplexer models, and a general treatment of these is given, along with that of Markov modulated arrivals. Particular attention is paid to the calculation of the prefactor .     

Prediction in Markovian bulk arrival queues

This paper deals with the statistical analysis of bulk arrival queues from a Bayesian point of view. The focus is on prediction of the usual measures of performance of the system in equilibrium. Posterior predictive distribution of the number of customers in the system is obtained through its probability generating function. Posterior distribution of the waiting time, in the queue and in the system, of the first customer of an arriving group is expressed in terms of their Laplace and Laplace–Stieltjes transform. Discussion of numerical inversion of these transforms is addressed.     

Perturbation bounds and truncations for a class of Markovian queues

We consider time-inhomogeneous Markovian queueing models with batch arrivals and group services. We study the mathematical expectation of the respective queue-length process and obtain the bounds on the rate of convergence and error of truncation of the process. Specific queueing models are shown as examples.     

Traffic processes in a class of finite Markovian queues

This paper exposes the stochastic structure of traffic processes in a class of finite state queueing systems which are modeled in continuous time as Markov processes. The theory is presented for theM/E _k /φ/L class under a wide range of queue disciplines. Particular traffic processes of interest include the arrival, input, output, departure and overflow processes. Several examples are given which demonstrate that the theory unifies many earlier works, as well as providing some new results. Several extensions to the model are discussed.     

Poisson's equation for queues driven by a Markovian marked point process

LetV _t be the virtual waiting time at timet in a queue having marked point process input generated by a finite Markov process {J_t}, such that in addition to Markovmodulated Poisson arrivals there may also be arrivals at jump times of {J_t}. In this setting, Poisson's equation isA g=–f whereA is the infinitesimal generator of {(V_t, J_t)}. It is shown that the solutiong can be expressed asKf for some suitable kernelK, and the explicit form ofK is evaluated. The results are applied to compute limiting variance constants for (normalized) time averages of functionsf(V _t, J_t), in particularf(V _t,J_t)=V_t.     

Approximations for Markovian multi-class queues with preemptive priorities

We discuss the approximation of performance measures in multi-class M/M/k queues with preemptive priorities for large problem instances (many classes and servers) using class aggregation and server reduction. We compared our approximations to exact and simulation results and found that our approach yields small-to-moderate approximation errors.     

Abandonment versus blocking in many-server queues: asymptotic optimality in the QED regime

We consider a controlled queueing system of the $G/M/n/B+GI$ G / M / n / B + G I type, with many servers and impatient customers. The queue-capacity $B$ B is the control process. Customers who arrive at a full queue are blocked and customers who wait too long in the queue abandon. We study the tradeoff between blocking and abandonment, with cost accumulated over a random, finite time-horizon, which yields a queueing control problem (QCP). In the many-server quality and efficiency-driven (QED) regime, we formulate and solve a diffusion control problem (DCP) that is associated with our QCP. The DCP solution is then used to construct asymptotically optimal controls (of the threshold type) for QCP. A natural motivation for our QCP is telephone call centers, hence the QED regime is natural as well. QCP then captures the tradeoff between busy signals and customer abandonment, and our solution specifies an asymptotically optimal number of trunk-lines.     

Equilibrium balking strategies in Markovian queues with working vacations

The equilibrium balking strategies are investigated in the paper for observable and unobservable single-server queues with working vacations. In such an M/M/1 queue with working vacations, the server undertakes the workload with a lower service rate rather than completely stops to work during the vacation period. Upon arrival, the customers decide whether to join or balk the queue based on observation of the queue length and the status of the server, along with the reward-cost structure of the system. Accordingly, four cases with respect to different levels of information are studied and the corresponding Nash equilibria are derived. Finally, the effect of the information levels as well as several parameters on the equilibrium threshold and equilibrium entrance probabilities is illustrated by numerical examples.     

Moments of claims in a Markovian environment

This paper considers discounted aggregate claims when the claim rates and sizes fluctuate according to the state of the risk business. We provide a system of differential equations for the Laplace–Stieltjes transform of the distribution of discounted aggregate claims under this assumption. Using the differential equations, we present the first two moments of discounted aggregate claims in a Markovian environment. We also derive simple expressions for the moments of discounted aggregate claims when the Markovian environment has two states. Numerical examples are illustrated when the claim sizes are specified.     

A sequential technique for the control of traffic intensity in Markovian queues

A sequential parameter control technique previously introduced by the author is modified in this paper so as to make it simple in practice. The detailed procedure involving two phases, a warning phase with control limits and a testing phase using an appropriate test is illustrated for a queueing system with an embedded Markov chain. Operating characteristics of the procedure are also examined.     

Approximations for Time-Dependent Distributions in Markovian Fluid Models

In this paper we analyse Markov-modulated fluid processes over finite time intervals. We study the joint distribution of the level at time \(\theta < \infty \) and of the maximum level over [0, θ], as well as the joint distribution of the level at time θ and the minimum level over [0, θ]. We approximate θ by a random variable T with Erlang distribution and so use an approach different from the usual Laplace transform to compute the distributions. We present probabilistic interpretation of the equations and provide a numerical illustration.