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Related papers: Omnithermal Perfect Simulation for Multi-server Qu…

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In this paper we describe a perfect simulation algorithm for the stable $M/G/c$ queue. Sigman (2011: Exact Simulation of the Stationary Distribution of the FIFO M/G/c Queue. Journal of Applied Probability, 48A, 209--213) showed how to build…

Probability · Mathematics 2015-12-02 Stephen B. Connor , Wilfrid S. Kendall

We introduce the first class of perfect sampling algorithms for the steady-state distribution of multi-server queues with general interarrival time and service time distributions. Our algorithm is built on the classical dominated coupling…

Probability · Mathematics 2015-08-11 Jose Blanchet , Jing Dong , Yanan Pei

In this paper, we introduce a slight variation of the Dominated Coupling From the Past algorithm (DCFTP) of Kendall, for bounded Markov chains. It is based on the control of a (typically non-monotonic) stochastic recursion by a (typically…

Probability · Mathematics 2026-01-14 Thomas Masanet , Pascal Moyal

We present the first class of perfect sampling (also known as exact simulation) algorithms for the steady-state distribution of non-Markovian loss networks. We use a variation of Dominated Coupling From The Past for which we simulate a…

Probability · Mathematics 2013-12-17 Jose Blanchet , Jing Dong

We provide the first algorithm that under minimal assumptions allows to simulate the stationary waiting-time sequence of a single-server queue backwards in time, jointly with the input processes of the queue (inter-arrival and service…

Probability · Mathematics 2015-01-22 Jose Blanchet , Aya Wallwater

Using a result of Blanchet and Wallwater (2015: Exact sampling of stationary and time-reversed queues. ACM TOMACS, 25, 26) for exactly simulating the maximum of a negative drift random walk queue endowed with independent and identically…

Probability · Mathematics 2019-06-06 Jose Blanchet , Yanan Pei , Karl Sigman

Parallel algorithms designed for simulation and performance evaluation of single-server tandem queueing systems with both infinite and finite buffers are presented. The algorithms exploit a simple computational procedure based on recursive…

Numerical Analysis · Mathematics 2012-11-30 Sergei M. Ermakov , Nikolai K. Krivulin

Determinantal point processes (DPP) serve as a practicable modeling for many applications of repulsive point processes. A known approach for simulation was proposed in \cite{Hough(2006)}, which generate the desired distribution point wise…

Probability · Mathematics 2013-11-06 Laurent Decreusefond , Ian Flint , Kah Choon Low

We define a wide class of Markovian load balancing networks of identical single-server infinite-buffer queues. These networks may implement classic parallel server or work stealing load balancing policies, and may be asymmetric, for…

Networking and Internet Architecture · Computer Science 2024-07-08 Carl Graham

Motivated by the growing interest in today's massive parallel computing capabilities we analyze a queueing network with many servers in parallel to which jobs arrive a according to a Poisson process. Each job, upon arrival, is split into…

Probability · Mathematics 2015-07-20 Mariana Olvera-Cravioto , Octavio Ruiz-Lacedelli

Fork-join network is a class of queueing networks with applications in manufactory, healthcare and computation systems. In this paper, we develop a simulation algorithm that (1) generates i.i.d. samples of the job sojourn time, jointly with…

Probability · Mathematics 2016-07-05 Xinyun Chen , Xianjun Shi

Fast and accurate optimization and simulation is widely becoming a necessity for large scale transmission resiliency and planning studies such as N-1 SCOPF, batch contingency solvers, and stochastic power flow. Current commercial tools,…

Systems and Control · Electrical Eng. & Systems 2021-03-30 Aayushya Agarwal , Amritanshu Pandey , Larry Pileggi

Max-algebra models of tandem single-server queueing systems with both finite and infinite buffers are developed. The dynamics of each system is described by a linear vector state equation similar to those in the conventional linear systems…

Numerical Analysis · Mathematics 2012-11-27 N. K. Krivulin

We give a new method for generating perfectly random samples from the stationary distribution of a Markov chain. The method is related to coupling from the past (CFTP), but only runs the Markov chain forwards in time, and never restarts it…

Probability · Mathematics 2012-06-19 David B. Wilson

In this paper, we use a machine learning approach to predict the stationary distributions of the number of customers in a single-staiton multi server system. We consider two systems, the first is $c$ homogeneous servers, namely the…

Performance · Computer Science 2025-04-03 Eliran Sherzer

The advent of digital twins (DT) for the control and management of communication networks requires accurate and fast methods to estimate key performance indicators (KPI) needed for autonomous decision-making. Among several alternatives,…

Networking and Internet Architecture · Computer Science 2024-05-29 Franco Coltraro , Marc Ruiz , Luis Velasco

Finite-capacity single-server queues with general service-time distributions form the backbone of numerous real-world systems, yet classical simulation of performance metrics such as blocking probabilities and delay becomes computationally…

Quantum Physics · Physics 2025-12-12 Or Peretz , Michal Koren , Nir Perel

We consider perfect simulation algorithms for locally stable point processes based on dominated coupling from the past, and apply these methods in two different contexts. A new version of the algorithm is developed which is feasible for…

Methodology · Statistics 2010-03-02 Graeme K. Ambler , Bernard W. Silverman

Gaitonde and Tardos recently studied a model of queueing networks where queues compete for servers and re-send returned packets in future rounds. They quantify the amount of additional processing power that guarantees a decentralized…

Computer Science and Game Theory · Computer Science 2022-10-18 Hu Fu , Qun Hu , Jia'nan Lin

Deploying trustworthy AI systems requires principled uncertainty quantification. Conformal prediction (CP) is a widely used framework for constructing prediction sets with distribution-free coverage guarantees. In many practical settings,…

Machine Learning · Computer Science 2026-03-18 Haifeng Wen , Osvaldo Simeone , Hong Xing
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