The analysis of cyclic stochastic fluid flows with time-varying transition rates
From MaRDI portal
Publication:257056
DOI10.1007/s11134-015-9456-8zbMath1332.76041OpenAlexW1679554665MaRDI QIDQ257056
Barbara Margolius, Małgorzata M. O'Reilly
Publication date: 15 March 2016
Published in: Queueing Systems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11134-015-9456-8
cyclic stochastic fluid modelnonstationary queuesqueues with time-varying arrivalsstochastic fluid model
Queues and service in operations research (90B22) Stochastic analysis applied to problems in fluid mechanics (76M35)
Related Items (2)
Stationary distributions for a class of Markov-modulated tandem fluid queues ⋮ Networks of interacting stochastic fluid models with infinite and finite buffers
Cites Work
- Unnamed Item
- Unnamed Item
- The \(G_{t}/GI/s_{t}+GI\) many-server fluid queue
- Large-time asymptotics for the \(G_{t}/M_{t}/s_{t}+GI_{t}\) many-server fluid queue with abandonment
- The matrices R and G of matrix analytic methods and the time-inhomogeneous periodic quasi-birth-and-death process
- Algorithms for the Laplace-Stieltjes transforms of first return times for stochastic fluid flows
- Fluid models in queueing theory and Wiener-Hopf factorization of Markov chains
- Hitting probabilities and hitting times for stochastic fluid flows
- Algorithms for Time-Varying Networks of Many-Server Fluid Queues
- A Network of Time-Varying Many-Server Fluid Queues with Customer Abandonment
- Stationary distributions for fluid flow models with or without brownian noise
- How and Why to Solve the Operator Equation AX −XB = Y
- Fluid Flow Models and Queues—A Connection by Stochastic Coupling
- Transient Analysis of Fluid Flow Models via Stochastic Coupling to a Queue
- ALGORITHMS FOR RETURN PROBABILITIES FOR STOCHASTIC FLUID FLOWS
- Efficient algorithms for transient analysis of stochastic fluid flow models
This page was built for publication: The analysis of cyclic stochastic fluid flows with time-varying transition rates