Closed queueing networks under congestion: non-bottleneck independence and bottleneck convergence

We analyze the behavior of closed product-form queueing networks when the number of customers grows to infinity and remains proportionate on each route (or class). First, we focus on the stationary behavior and prove the conjecture that the stationary distribution at non-bottleneck queues converges weakly to the stationary distribution of an ergodic, open product-form queueing network. This open network is obtained by replacing bottleneck queues with per-route Poissonian sources whose rates are determined by the solution of a strictly concave optimization problem. Then, we focus on the transient behavior of the network and use fluid limits to prove that the amount of fluid, or customers, on each route eventually concentrates on the bottleneck queues only, and that the long-term proportions of fluid in each route and in each queue solve the dual of the concave optimization problem that determines the throughputs of the previous open network.Comment: 22 page

Strategic experimentation in queues

We analyze the social and private learning at the symmetric equilibria of a queueing game with strategic experimentation. An infinite sequence of agents arrive at a server which processes them at an unknown rate. The number of agents served at each date is either: a geometric random variable in the good state, or zero in the bad state. The queue lengthens with each new arrival and shortens if the agents are served or choose to quit the queue. Agents can only observe the evolution of the queue after they arrive; they, therefore, solve a strategic experimentation problem when deciding how long to wait to learn about the probability of service. The agents, in addition, benefit from an informational externality by observing the length of the queue and the actions of other agents. They also incur a negative payoff externality, as those at the front of the queue delay the service of those at the back. We solve for the long-run equilibrium behavior of this queue and show there are typically mass exits from the queue, even if the server is in the good state

Journeys in the City: Empathising With the Users of Transport Buildings

Accessibility is a considerable and growing issue in the design of many public buildings including vital high use buildings such as train stations. Yet research methods for these buildings are poor. This paper suggests that one new approach to design is to use immersive, auto-ethnographic methods to achieve an empathetic understanding of design needs. The paper asks: what can we learn about the mobility requirements of station users when we are immersed in a train station environment, and what mobile research methods can we use to begin to explore this? The paper reports on a study that used video diaries to explore Canary Wharf Station in a November evening rush hour in dry conditions, and specifically to study passenger behaviours on an island platform within the station. The analysis focused on how to improve mobility in the station from a user’s perspective. This use of auto-ethnography is discussed as part of a broader methodological debate about how to explore universal design issues from a user’s perspective, and in the context of empathetic desig

Herding in Queues with Waiting Costs: Rationality and Regret

We study how consumers with waiting cost disutility choose between two congested services of unknown service value. Consumers observe an imperfect private signal indicating which service facility may provide better service value as well as the queue lengths at the service facilities before making their choice. If more consumers choose the same service facility because of their private information, longer queues will form at that facility and indicate higher quality. On the other hand, a long queue also implies more waiting time. We characterize the equilibrium queue-joining behavior of arriving consumers and the extent of their learning from the queue information in the presence of such positive and negative externalities. We find that when the arrival rates are low, utility-maximizing rational consumers herd and join the longer queue, ignoring any contrary private information. We show that even when consumers treat queues as independently evolving, herd behavior persists with consumers joining longer queues above a threshold queue difference. However, if the consumers seek to minimize ex post regret when making their decisions, herd behavior may be dampened

Equilibrium in Queues Under Unknown Service Times and Service Value

In the operations research literature, the queue joining probability is monotonic decreasing in the queue length; the longer the queue, the fewer consumers join. Recent academic and empirical evidence indicates that queue-joining probabilities may not always be decreasing in the queue length. We provide a simple explanation for these nonmonotonic queue-joining strategies by relaxing the informational assumptions in Naor\u27s model. Instead of imposing that the expected service time and service value are common knowledge, we assume that they are unknown to consumers, but positively correlated. Under such informational assumptions, the posterior expected waiting cost and service value increase in the observed queue length. As a consequence, we show that queue-joining equilibria may emerge for which the joining probability increases locally in the queue length. We refer to these as “sputtering equilibria.” We discuss when and why such sputtering equilibria exist for discrete as well as continuously distributed priors on the expected service time (with positively correlated service value)

Estimating customer impatience in a service system with unobserved balking

This paper studies a service system in which arriving customers are provided with information about the delay they will experience. Based on this information they decide to wait for service or to leave the system. The main objective is to estimate the customers' patience-level distribution and the corresponding potential arrival rate, using knowledge of the actual queue-length process only. The main complication, and distinguishing feature of our setup, lies in the fact that customers who decide not to join are not observed, but, remarkably, we manage to devise a procedure to estimate the load they would generate. We express our system in terms of a multi-server queue with a Poisson stream of customers, which allows us to evaluate the corresponding likelihood function. Estimating the unknown parameters relying on a maximum likelihood procedure, we prove strong consistency and derive the asymptotic distribution of the estimation error. Several applications and extensions of the method are discussed. The performance of our approach is further assessed through a series of numerical experiments. By fitting parameters of hyperexponential and generalized-hyperexponential distributions our method provides a robust estimation framework for any continuous patience-level distribution

Pilot interaction with automated airborne decision making systems

An investigation was made of interaction between a human pilot and automated on-board decision making systems. Research was initiated on the topic of pilot problem solving in automated and semi-automated flight management systems and attempts were made to develop a model of human decision making in a multi-task situation. A study was made of allocation of responsibility between human and computer, and discussed were various pilot performance parameters with varying degrees of automation. Optimal allocation of responsibility between human and computer was considered and some theoretical results found in the literature were presented. The pilot as a problem solver was discussed. Finally the design of displays, controls, procedures, and computer aids for problem solving tasks in automated and semi-automated systems was considered

Stochastic approximation of symmetric Nash equilibria in queueing games

We suggest a novel stochastic-approximation algorithm to compute a symmetric Nash-equilibrium strategy in a general queueing game with a finite action space. The algorithm involves a single simulation of the queueing process with dynamic updating of the strategy at regeneration times. Under mild assumptions on the utility function and on the regenerative structure of the queueing process, the algorithm converges to a symmetric equilibrium strategy almost surely. This yields a powerful tool that can be used to approximate equilibrium strategies in a broad range of strategic queueing models in which direct analysis is impracticable

ASIdE: Using Autocorrelation-Based Size Estimation for Scheduling Bursty Workloads.

Temporal dependence in workloads creates peak congestion that can make service unavailable and reduce system performance. To improve system performability under conditions of temporal dependence, a server should quickly process bursts of requests that may need large service demands. In this paper, we propose and evaluateASIdE, an Autocorrelation-based SIze Estimation, that selectively delays requests which contribute to the workload temporal dependence. ASIdE implicitly approximates the shortest job first (SJF) scheduling policy but without any prior knowledge of job service times. Extensive experiments show that (1) ASIdE achieves good service time estimates from the temporal dependence structure of the workload to implicitly approximate the behavior of SJF; and (2) ASIdE successfully counteracts peak congestion in the workload and improves system performability under a wide variety of settings. Specifically, we show that system capacity under ASIdE is largely increased compared to the first-come first-served (FCFS) scheduling policy and is highly-competitive with SJF. © 2012 IEEE