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A discrete event simulation model for evaluating the performances of an m/g/c/c state dependent queuing system
Ruzelan Khalid1, Mohd Kamal M Nawawi, Luthful A Kawsar
1School of Quantitative Sciences, Universiti Utara Malaysia, Sintok, Kedah, Malaysia.
Plos One
|April 6, 2013
Summary
This study addresses limitations in discrete simulation software for state-dependent queuing networks. A novel approach in Arena software models dynamic service rates, revealing discrepancies between simulation and analytical results at specific arrival rates.
Area of Science:
- Operations Research
- Computer Simulation
- Queueing Theory
Background:
- Modern Discrete Simulation System (DES) software lacks support for modeling dynamic service rates in state-dependent queuing networks.
- State-dependent queuing networks, such as M/G/C/C models, are crucial for analyzing systems with variable entity populations.
Purpose of the Study:
- To design and implement a novel approach for modeling M/G/C/C state-dependent queuing networks in Arena software.
- To evaluate the impact of varying arrival rates on key performance metrics within a complex network topology.
Main Methods:
- Developed a custom approach to overcome DES software limitations in modeling state-dependent service rates.
- Constructed an M/G/C/C state-dependent queuing model using Arena simulation software.
- Analyzed system performance by varying arrival rates and comparing simulation outputs with analytical predictions.
Main Results:
- Identified specific ranges of arrival rates where simulation results exhibit significant fluctuations across replications.
- Observed discrepancies between simulation and analytical results, particularly within these volatile arrival rate ranges.
- Quantified the impact of arrival rates on throughput, blocking probability, expected service time, and the number of entities in the network.
Conclusions:
- The developed model successfully simulates M/G/C/C state-dependent queuing networks, highlighting practical limitations of standard DES software.
- Understanding the identified arrival rate ranges is critical for accurate simulation modeling and analysis of complex systems.
- Further investigation into the scientific justifications for simulation-analytical discrepancies is warranted for improved modeling accuracy.
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