Introduction to Simulation and SLAM II (3rd ed.)
Introduction to Simulation and SLAM II (3rd ed.)
Fundamentals of queueing theory (2nd ed.).
Fundamentals of queueing theory (2nd ed.).
Numerical transient analysis of Markov models
Computers and Operations Research
Some effects of nonstationarity on multiserver Markovian queueing systems
Operations Research
The Markov-modulated Poisson process (MMPP) cookbook
Performance Evaluation
Real Time Network Management
Control and Performance in Packet, Circuit, and ATM Networks
Control and Performance in Packet, Circuit, and ATM Networks
Transient diffusion approximation for some queuening systems.
SIGMETRICS '83 Proceedings of the 1983 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Dynamic bandwidth allocation in broadband-ISDN using a multilevel optimal control approach
INFOCOM '95 Proceedings of the Fourteenth Annual Joint Conference of the IEEE Computer and Communication Societies (Vol. 3)-Volume - Volume 3
Modeling the Dynamics of the RED Algorithm
QofIS '00 Proceedings of the First COST 263 International Workshop on Quality of Future Internet Services
Modeling the time varying behavior of mobile ad-hoc networks
MSWiM '04 Proceedings of the 7th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
QoS-oriented control of server systems
Proceedings of the Fifth International Workshop on Feedback Control Implementation and Design in Computing Systems and Networks
QoS-oriented control of server systems
ACM SIGOPS Operating Systems Review
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Evaluation of the behavior of queues with nonstationary arrival processes is of importance in several applications including communication networks. However, the analysis of nonstationary queues is in general computationally complex, and seldom produces closed form expressions. Thus approximation methods may be more appropriate. In this paper, the pointwise stationary fluid flow approximation (PSFFA) for determining the mean queue length of nonstationary queues is presented. The PSFFA combines steady state queueing results with a simple fluid flow model to develop a single nonlinear differential equation model of the queue. Numerical integration techniques are used to solve the PSFFA model and the method is illustrated by several examples. The power of this approach is that at can handle very general queueing systems.