Queueing Theory is a vibrant research area, at the interface of Applied Probability and Stochastic Operations Research. It is concerned with resource contention in service systems, as well as the resulting congestion dynamics, with probability theory being the main analytic tool. Time and again, performance questions in areas like computer-communications, data centers, traffic & transportation, manufacturing, warehousing and healthcare logistics give rise to challenging queueing problems; and their solution invariably involves novel modeling paradigms and innovative methodological approaches.

Recognizing the strong need for a journal focused on both theory and applications of queueing systems, Uma Prabhu (Cornell University) founded Queueing Systems in 1986. This EURANDOM workshop celebrates its 40th anniversary, and brings together leading international experts, including a significant number of editorial board members of Queueing Systems, to discuss recent developments and exciting new frontiers in queueing theory.

Organizers

• Sem Borst (Eindhoven University of Technology)
• Onno Boxma (Eindhoven University of Technology)
• Michel Mandjes (Leiden University and University of Amsterdam)

Speakers

The workshop program will feature about 18 lectures, with both invited talks and contributed presentations based on papers which have been submitted for a special issue of Queueing Systems: 40 Years of QUESTA. Bert Zwart serves as coordinating editor for the special issue, along with Sergey Foss, Petar Momcilovic, and Weina Wang as further guest editors.

Programme

The programme starts on Wednesday 27 May at 10.00h and will end on Friday 29 May after lunch. On Wednesday a conference dinner will be organised.

Download here the detailed programme. All titles and abstracts can be found below the registration form.

Registration

You can register for the workshop using the form below. Coffee / tea and lunch are included in the registration fee.

After registering, you will immediately receive an automatic confirmation of your registration (check your spam folder!). Your proof of payment will be sent separately, in the week following the workshop.

Registration closes on Tuesday 19 May 2026.

Abstracts

Ivo Adan

Call center model with heterogeneous reneging customers.
We consider a queueing model of a call center with reneging. There are two types of customers: patient and impatient. The patient customers renege at a slower rate than the impatient customers. We study the queueing time process in this system, the transform of which satisfies a recursion with multiple recursive terms and show how such recursions can be solved.

Anton Braverman

On the Accuracy of Diffusion Approximations for Queueing Models with General Primitives
Despite their widespread use, the accuracy of diffusion approximations for queueing systems with general primitives remains poorly understood. This talk explores this gap. A unifying message emerges: diffusion error decomposes naturally into interior and boundary terms. Interior terms are strikingly universal—they can be controlled using only low-order moments of the system primitives. Boundary terms, by contrast, are fundamentally more delicate: while crude bounds are relatively easy to obtain, achieving sharp (order-optimal) bounds requires deeper, model-specific insight.
The analysis hinges on extending the generator approach of Stein’s method beyond continuous-time Markov chains to piecewise-deterministic Markov processes (PDMPs). In this setting, the infinitesimal generator alone no longer suffices to characterize the stationary distribution; instead, we work with the basic adjoint relationship (BAR), which provides the appropriate stationary balance equation for PDMPs.

Céline Comte

Admission Control of Quasi-Reversible Queueing Systems: Optimization and Reinforcement Learning
In this talk, we introduce a versatile scheme for optimizing the arrival rates of quasi-reversible queueing systems. We first propose an alternative definition of quasi-reversibility that encompasses reversibility and highlights the importance of the definition of customer classes. Then we introduce balanced arrival control policies, which generalize the notion of balanced arrival rates introduced in the context of Whittle networks, to the much broader class of quasi-reversible queueing systems. We prove that supplementing a quasi-reversible queueing system with a balanced arrival-control policy preserves the quasi-reversibility, and we specify the form of the stationary measures. We revisit two canonical examples of quasi-reversible queueing systems, Whittle networks and order-independent queues. Lastly, we focus on the problem of admission control and leverage our results in the frameworks of optimization and reinforcement learning.
This presentation is based on a joint work with Pascal Moyal (Institut Élie Cartan de Lorraine).

Krzysztof Dębicki

Queuing networks in multi-scale light and heavy traffic regime
We study a queueing network with a strictly upper-triangular routing matrix, where each column contains at most one non-negative entry.
The root node receives input from a Gaussian process with stationary increments or a spectrally positive Lévy process.
Our aim is to characterize the distribution of the multivariate stationary workload under a specific scaling of the service rates, in both light and heavy traffic parameterization. In particular, we establish conditions under which certain queueing workloads
within the network asymptotically decouple, becoming independent in the limiting regime.
Joint work with Nikolai Kriukov and Michel Mandjes.

Sergey Foss

On Recurrence of the Infinite Server Queue
The talk concerns the recurrence structure of the infinite server queue, as viewed through the prism of the maximum dater sequence, namely the time to drain the current work in the system as seen at arrival epochs. Despite the importance of this model in queueing theory, we are aware of no complete analysis of the stability behavior of this model, especially in settings in which either or both the inter arrival and service time distributions have infinite mean. In this talk, we present the analogue of the Loynes construction of the stationary version in the context of stationary ergodic inputs, extending earlier work of E.Altman (2005), and then classify the Markov chain when the inputs are independent and identically distributed. This allows us to classify the chain, according to transience, recurrence in the sense of Harris, and positive recurrence in the sense of Harris. We further comment on the  tail asymptotics for the stationary distribution of the maximum dater sequence, when the service times have tails that are asymptotically exponential or Pareto, and we contrast the stability theory for the infinite server queue relative to that for the single server queue.
Joint work with Peter Glynn.

Rouba Ibrahim

Delay Information in Non-Stationary Priority Queues
This talk examines the operational impact of providing queue position information in priority queueing systems with time-varying arrivals. We model a two-class, multi-server queue using fluid approximations to compare performance under “no information” (perceived positions) versus “full information” (true positions). We prove the stability of a periodic fluid equilibrium and demonstrate that providing information does not uniformly improve performance. Instead, it introduces trade-offs between queue length and abandonment, both within and across priority classes, particularly when demand fluctuates. Our results suggest that the optimal information policy depends on system load and cost structures, and that effective information design may require class-specific disclosure to mitigate these trade-offs.
This work is joint with Philipp Afeche, Junqi Hu, and Vahid Sarhangian.

Offer Kella

M/G/1+D perishable inventory systems
We consider a Perishable Inventory System (PIS) in which demands for items arrive according to a Poisson process and items according to a renewal process. Stored items have a deterministic maximum lifetime ‘on the shelf’.
Exploiting a relation between the so-called Virtual Out dating Time (VOT) process of this PIS and the workload process of the M/G/1+D queue, we prove a decomposition property of each of these two processes.
Subsequently we analyze two generalizations of the above PIS, where the quality of items on the shelf is not constant. In the first one there are two types of items, with different maximum lifetimes. In the second, the quality of an item gradually deteriorates with age.
Joint work with Onno Boxma, David Perry and Wolfgang Stadje.

Yoav Kerner

Opaque service: the case of server selection by strategic customers
We study a multi-server strategic queueing model in which customers choose among servers that differ in service rates and service valuations. Customers can either commit to a specific server or adopt a flexible strategy by joining multiple queues simultaneously. Service is received from the server that completes the request first, after which redundant requests are canceled. This flexibility option presents a clear trade-off: customers benefit from potentially shorter waiting times, but risk receiving lower-quality service from less desirable servers. We assume that customers are strategic, and we characterize the Nash equilibrium outcomes of this strategic queueing game. Our analysis demonstrates that although customers act to maximize their own welfare, introducing the flexibility option leads to higher overall social welfare. We further examine the socially optimal allocation and the revenue maximizing pricing strategy when flexibility is offered at a price.
Joint work with Binyamin Oz and Seva Shneer

Pascal Moyal

A general functional CLT for Lipschitz functionals of Poisson measures. Applications to queueing processes and Hawkes processes
In this talk, we will present a general functional central limit theorem (CLT) for stochastic processes defined as Lipschitz functionals of Poisson random measures. This result extends existing convergence results for solutions of SDE’s driven by Poisson measures, to the Brownian motion, for various distances, using the Stein method. The arguments of the proofs involve Malliavin calculus for Point processes, and even provide bounds for the speed of convergence in the functional CLT. These results can be applied to a wide class of stochastic processes representing queueing systems, biological or epidemiological processes, and Hawkes processes.
Joint work for Eustache Besançon, Laure Coutin and Laurent Decreusefond.

Yoni Nazarathy

Outputs processes of Queues, their Asymptotic Variance, and BRAVO
We present some results related to the asymptotic variance of counts of queueing output processes. In particular, a phenomenon termed BRAVO (Balancing Reduces Asymptotic Variance of Outputs), occurs in quite a few systems at the critical regime. With BRAVO, the long term variability of counts exhibits a decrease when a queueing system is set to criticality in comparison to cases where the system is not critical. We survey some results related to asymptotic variance and BRAVO and then focus on a recently derived formula associated with the asymptotic variance of counts of thinned birth and death processes.
The recent work is in collaboration with the late Daryl J Daley, and Jiesen Wang. 

Guodong Pang

Ergodic risk-sensitive admission control of Markovian multi-server queues with abandonment
We consider the ergodic risk-sensitive admission control problem for a Markovian multi-server queueing system with abandonment, where costs are incurred for server idleness, customer abandonment, and rejecting incoming arrivals. We first derive the Bellman optimality equation for this problem and show that a threshold policy—one that rejects incoming arrivals whenever the system-size exceeds a threshold—is optimal among all admissible control policies. We then propose a policy iteration algorithm to identify the optimal threshold, where we prove, under certain conditions on the problem’s parameters, that the algorithm will terminate at the optimal threshold level. We also characterize the effect of risk-sensitivity on the optimal threshold, proving that this threshold monotonically decreases with respect to the sensitivity parameter and converges to the average-cost optimal threshold from below as the sensitivity parameter tends to zero.

Kilian Raschel

Boundary contacts for reflected random walks in the quarter plane
We study reflected random walks in the quarter plane, with a focus on the time spent on the boundary axes. When the drift points into the cone, the boundary local time converges, without rescaling, to a non-trivial limiting random variable. In this talk, I will describe the structure of these limiting distributions and present several approaches to address this problem. In particular, I will show how the compensation approach (originally introduced in the 1990s to compute stationary distributions of reflected random walks) can be applied in this new context. The results will be illustrated through several examples.

Kavita Ramanan

Large deviations for interacting particle systems on sparse graphs

Liron Ravner

Nonparametric estimation of the jump-size distribution for M/G/1-type queues
In this talk we will discuss non-parametric estimation for the cumulative distribution function (CDF) of the job-size distribution for a queue with compound Poisson input. The workload process is observed according to an independent Poisson sampling process. The nonparametric estimator is constructed by first estimating the characteristic function (CF) and then applying an inversion formula. The convergence rate of the CF estimator at $s$ is shown to be of the order of $s^2/n$, where $n$ is the sample size. This convergence rate is leveraged to explore the bias-variance tradeoff of the inversion estimator. It is demonstrated that within a certain class of continuous distributions, the risk, in terms of MSE, is uniformly bounded by $C n^{-\frac{\eta}{1+\eta}}$, where $C$ is a positive constant and the parameter $\eta>0$ depends on the smoothness of the underlying class of distributions. A heuristic method is further developed to address the case of an unknown rate of the compound Poisson input process. Finally, we will discuss some natural extensions and related inversion problems.

Ziv Scully

New Scheduling and Dispatching Algorithms for Optimizing Tail Latency in Light-Tailed Queues
Many fundamental questions about optimizing tail latency in queues remain open. For instance, in even the simplest theoretical scheduling models, e.g. the light-tailed M/G/1, it is unknown how to schedule to minimize a given latency quantile, e.g. the 99th percentile. But recently, queueing theory has made rapid progress on optimizing asymptotic tail latency, i.e. the scaling of the 99.9…9th percentile in the “many-nine limit”, producing the following outcomes:

• A new scheduling algorithm that has provably optimal asymptotic tail latency. It also has state-of-the-art practical latency quantiles in simulation. The algorithm, called Boost, is a simple priority policy that assigns a job’s priority as a function of its arrival time and (possibly estimated) processing time.
• A new dispatching algorithm that mimics the new scheduling algorithm using only immediate dispatching to FCFS queues.
• A new tail metric that avoids the “cliffs” common in other tail metrics, and which is the key idea that leads to the new algorithms. The new metric is the average over jobs of an exponential function of latency with a carefully chosen growth rate.

This talk will give an overview of this recent progress. So far, our understanding is most complete for known processing times and single-server systems, but we will also discuss the results we have so far for unknown processing times and multi-server systems.

Fiona Sloothaak

Scale-Free Cascades in Dynamic Flow Networks
Scale-free congestion and disruption patterns are widely observed in real-world networks, including power-grid blackouts, traffic jams in transportation systems, and congestion in communication networks. Despite their prevalence, the mechanisms underlying these extreme events remain poorly understood. Classical explanations typically attribute such phenomena to network topology and critical capacity thresholds. In this talk, we introduce a universal and analytically tractable model of overload cascades in dynamic flow networks. We show that scale-free disruption sizes naturally arise from Pareto-tailed external inputs, through the principle of the fewest big jumps from extreme value theory. Our analysis combines the fewest-big-jumps principle with asymptotic analysis, drawing on mathematical techniques long used in the queueing literature. These results highlight a promising avenue for applying well-understood concepts in queueing to the study of cascading disruptions and congestion dynamics in flow networks.
Based on joint works with Agnieszka Janicka, Jeroen van Heijst, Sem Borst, Maria Vlasiou and Bert Zwart.

Alexander Stolyar

Cancel-on-completion redundancy in queues and related particle systems
We consider a class of systems, where n particles move on the real line. This class generalizes the model of a multi-server queueing system, employing so-called cancel-on-completion redundancy mechanism, but is motivated by other applications as well. In the queueing model: particles are servers and their locations are servers’ workloads; particles move to the left at constant speed and may jump to the right upon new job arrivals; the system is regulated at the left boundary point 0. The more general model allows regulation boundaries on either side, or both sides, or no regulation at all. We consider the mean-field asymptotic regime, where the number of particles n and the job arrival rates go to infinity, while the job arrival rates per particle remain constant. The system state for a given n is the empirical distribution of the particles’ locations. The results include: the existence/uniqueness of fixed points of mean-field limits (ML), which describe the limiting dynamics of the system; conditions for the concentration of the stationary distribution on an ML fixed point; the limits of the average velocity at which unregulated particle system advances. Our technical approach is such that the systems with different types of regulation are analyzed within a unified framework.

Bert Zwart

Insensitivity of Proportional Fairness in Critically Loaded Bandwidth Sharing Networks
Proportional fairness is a popular service allocation mechanism to describe and analyze the performance of data networks at flow level. Several authors have shown that the invariant distribution of networks operating according to proportional fairness admits a product form distribution under critical loading. They focus however on exponential job size distributions, leaving the case of general job size distributions as an open question. Motivated by this, we consider a network operating under proportional fairness where the job size distributions are of phase-type. We establish a heavy-traffic process limit theorem and show that the invariant distribution of the limit process is determined by the first moments of the job sizes only. Our analysis relies on a uniform convergence result for a fluid model.
Joint work with Maria Vlasiou (UT) and Jiheng Zhang (HKUST)

Financial support

The workshop is financially supported by NETWORKS and the Applied Probability Trust