Sequential Bottleneck Decomposition: An Approximation Method for Generalized Jackson Networks

In heavy traffic analysis of open queueing networks, processes of interest such as queue lengths and workload levels are generally approximated by a multidimensional reflected Brownian motion (RBM). Decomposition approximations, on the other hand, typically analyze stations in the network separately...

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Veröffentlicht in:	Operations research 1994-01, Vol.42 (1), p.119-136
Hauptverfasser:	Dai, J. G, Nguyen, Vien, Reiman, Martin I
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Approximation Brownian motion Covariance matrices Decomposition Exact sciences and technology Mathematical vectors Matrices networks: performance analysis of generalized Jackson networks Operational research and scientific management Operational research. Management science Operations research probability Queueing networks queues Queuing theory Queuing theory. Traffic theory stochastic model applications: heavy traffic and Brownian system model Stochastic models Studies Traffic Traffic congestion Traffic estimation Workloads
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