A Clustering Approximation Technique for Queueing Network Models with a Large Number of Chains
IEEE Transactions on Computers
Analysis of an Open Tandem Queueing Network with Population Constraint and Constant Service Times
MASCOTS '95 Proceedings of the 3rd International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
Product Form Queueing Networks
Performance Evaluation: Origins and Directions
Performance analysis of an ingress switch in a JumpStart optical burst switching network
Performance Evaluation
A tool for the analysis of hierarchical service-oriented extended open fork/join queueing networks
Proceedings of the 2nd international conference on Performance evaluation methodologies and tools
Solving Semi-Open Queuing Networks
Operations Research
Higher-order distributional properties in closed queueing networks
Performance Evaluation
SFM'07 Proceedings of the 7th international conference on Formal methods for performance evaluation
A fixed-point algorithm for closed queueing networks
EPEW'07 Proceedings of the 4th European performance engineering conference on Formal methods and stochastic models for performance evaluation
A multi-class closed queueing maintenance network model with a parts inventory system
Computers and Operations Research
Solving general multi-class closed queuing networks using parametric decomposition
Computers and Operations Research
| Hi-index | 0.01 |
In this paper, we present an approximate solution for the asymptotic behavior of relatively general queueing networks. In the particular case of networks with general service time distributions (i.e., fixed routing matrix, one or many servers per station, FIFO discipline), the application of the method gives relatively accurate results in a very short time. The approximate stationary state probabilities are identified with the solution of a nonlinear system. The proposed method is applicable to a larger class of queueing networks (dependent routing matrix, stations with fimite capacity, etc.). In this case, the structure of the network studied must satisfy certain decomposability conditions.