A general multiserver state-dependent queueing system

The work studies a general multiserver queue in which the service time of an arriving customer and the next interarrival period may depend on both the current waiting time and the server assigned to the arriving customer. Stability of the system is proved under general assumptions on the predetermined distributions describing the model. The proof exploits a combination of the Markov property of the workload process with a regenerative property of the process. The key idea leading to stability is a characterization of the limit behavior of the forward renewal process generated by regenerations. Extensions of the basic model are also studied

Analysis of finite-buffer state-dependent bulk queues

<p>In this paper, we consider a general state-dependent finite-buffer bulk queue in which the rates and batch sizes of arrivals and services are allowed to depend on the number of customers in queue and service batch sizes. Such queueing systems have rich applications in manufacturing, service operations, computer and telecommunication systems. Interesting examples include batch oven processes in the aircraft and semiconductor industry; serving of passengers by elevators, shuttle buses, and ferries; and congestion control mechanisms to regulate transmission rates in packet-switched communication networks. We develop a unifying method to study the performance of this general class of finite-buffer state-dependent bulk queueing systems. For this purpose, we use semi-regenerative analysis to develop a numerically stable method for calculating the limiting probability distribution of the queue length process. Based on the limiting probabilities, we present various performance measures for evaluating admission control and batch service policies, such as the loss probability for an arriving group of customers and for individual customers within a group. We demonstrate our method by means of numerical examples.</p>

Shot-noise queueing models

We provide a survey of so-called shot-noise queues: queueing models with the special feature that the server speed is proportional to the amount of work it faces. Several results are derived for the workload in an M/G/1 shot-noise queue and some of its variants. Furthermore, we give some attention to queues with general workload-dependent service speed. We also discuss linear stochastic fluid networks, and queues in which the input process is a shot-noise process

Service systems with balking based on queueing time

We consider service systems with balking based on queueing time, also called queues with wait-based balking. An arriving customer joins the queue and stays until served if and only if the queueing time is no more than some pre-specified threshold at the time of arrival. We assume that the arrival process is a Poisson process. We begin with the study of theM/G/1 system with a deterministic balking threshold. We use level-crossing argument to derive an integral equation for the steady state virtual queueing time (vqt) distribution. We describe a procedure to solve the equation for general distributions and we solve the equation explicitly for several special cases of service time distributions, such as phase type, Erlang, exponential and deterministic service times. We give formulas for several performance criteria of general interest, including average queueing time and balking rate. We illustrate the results with numerical examples. We then consider the first passage time problem in an M/PH/1 setting. We use a fluid model where the buffer content changes at a rate determined by an external stochastic process with finite state space. We derive systems of first-order linear differential equations for both the mean and LST (Laplace-Stieltjes Transform) of the busy period in the fluid model and solve them explicitly. We obtain the mean and LST of the busy period in the M/PH/1 queue with wait-based balking as a special limiting case of the fluid model. We illustrate the results with numerical examples. Finally we extend the method used in the single server case to multi-server case. We consider the vqt process in an M/G/s queue with wait-based balking. We construct a single server system, analyze its operating characteristics, and use it to approximate the multi-server system. The approximation is exact for the M/M/s and M/G/1 system. We give both analytical results and numerical examples. We conduct simulation to assess the accuracy of the approximation

Finite-buffer queues with workload-dependent service and arrival rates. Queueing Systems

We consider M/G/1 queues with workload-dependent arrival rate, service speed, and restricted accessibility. The admittance of customers typically depends on the amount of work found upon arrival in addition to its own service requirement. Typical examples are the finite dam, systems with customer impatience and queues regulated by the complete rejection discipline. Our study is motivated by queueing scenarios where the arrival rate and/or speed of the server depends on the amount of work present, like production systems and the Internet. First, we compare the steady-state distribution of the workload in two finite-buffer models, in which the ratio of arrival and service speed is equal. Second, we find an explicit expression for the cycle maximum in an M/G/1 queue with workload-dependent arrival and service rate. And third, we derive a formal solution for the steady-state workload density in case of restricted accessibility. The proportionality relation between some finite and infinite-buffer queues is extended. Level crossings and Volterra integral equations play a key role in our approach

Task allocation policies for State Dependent queues

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 108-111).Consider a model of a dynamical queue with deterministic arrival and service rates, where the service rate depends on the server utilization history. This proposed queueing model occurs in many practical situations. for example in human-in-the-loop systems where widely accepted empirical laws describe human performance as a function of mental arousal, which increases when the human is working on a task and decreases otherwise. Formal methods for task management in state-dependent dynamical queues are gathering increasing attention to improve the efficiency of such systems. The focus of this research is hence to design maximally stabilizing task release control policies to maximize the useful throughput of such a system. Assuming that the error probability of a server is also related to its state., the useful throughput can be defined as the number of successfully completed tasks per unit time. Monitoring of both service and error rates is particularly typical in the realm of human-in-the-loop and production systems. This research focuses on developing policies to minimize both these penalty measures. For a server with deterministic service rate, the optimal policy is found to be a threshold policy that releases a task to the server only when the server state is less than or equal to a certain threshold. Assuming homogeneous tasks that bring in the same deterministic amount of work to be done, it can be shown that an appropriate threshold policy is maximally stabilizing and that this threshold value can be uniquely determined. This work is then further extended to the case when the server behaves stochastically and verified using simulation. Finally, a proof-of-concept experiment is proposed and developed to test the feasibility of the proposed theoretical policies in real-world settings. The experiment consisted of completing multiple-choice verbal analogy questions and the results confirm the effect of workload control in improving human performance.by Christine Chiu Hsia Siew.S.M