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Simulation of large scale networks I: simulation of large-scale networks using SSF
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Source Winter Simulation Conference archive
Proceedings of the 35th conference on Winter simulation: driving innovation table of contents
New Orleans, Louisiana
SESSION: Modeling methodology a table of contents
Pages: 650 - 657  
Year of Publication: 2003
ISBN:0-7803-8132-7
Authors
David M. Nicol  University of Illinois at Urbana-Champaign, Urbana, IL
Jason Liu  University of Illinois at Urbana-Champaign, Urbana, IL
Michael Liljenstam  University of Illinois at Urbana-Champaign, Urbana, IL
Guanhua Yan  Dartmouth College, Hanover, NH
Sponsors
INFORMS/CS : Institute for Operations Research and the Management Sciences/College on Simulation
NIST : National Institute of Standards and Technology
IEEE/SMCS : Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
ACM: Association for Computing Machinery
(SCS) : The Society for Modeling and Simulation International
SIGSIM: ACM Special Interest Group on Simulation and Modeling
IIE : Institute of Industrial Engineers
IEEE/CS : Institute of Electrical and Electronics Engineers/Computer Society
ASA : American Statistical Association
Publisher
Winter Simulation Conference 
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Downloads (6 Weeks): 5,   Downloads (12 Months): 25,   Citation Count: 10
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ABSTRACT

Some applications of simulation require that the model state be advanced in simulation time faster than the wall-clock time advances as the simulation executes. This <i>faster than real-time</i> requirement is crucial, for instance, when a simulation is used as part of a real-time control system, working through the consequences of contemplated control actions, in order to identify feasible (or even optimal) decisions. This paper considers the issue of faster than real-time simulation of very large communication networks, and how this is accomplished using our implementation (in C++) of the Scalable Simulation Framework (SSF). Our tool (called iSSF) uses hierarchical levels of abstraction, <i>and</i> parallelism, to achieve speedups of <b>nearly four orders of magnitude</b>, enabling real-time execution rates on large network models. We quantify the effects that choice of hierarchical abstraction has on the simulation time advance rate, and show empirically how changing the abstraction mix affects the execution rate on a large network example.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Kesidis, G., A. Singh, D. Cheung, and W. Kwok. 1996, Nov.. Feasibility of fluid event-driven simulation for ATM networks. In IEEE Globecom 1996.
 
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Nicol, D., M. Goldsby, and M. Johnson. 1999, Oct.. Fluid-based simulation of communication networks using SSF. In Proceedings of the 1999 SCS European Simulation Conference. Erlangen, Germany.
 
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Nicol, D. M., and G. Yan. 2003. Discrete-event fluid modeling of TCP for background traffic. Submitted for publication.
 
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Ross, H. 1983. Stochastic processes. New York: Wiley.
 
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Ye, T., H. T. Kaur, S. Kalyanaraman, Kenneth, S. Vastola, and S. Yadav. 2002. Dynamic optimization of OSPF weights using online simulation.

CITED BY  10
 
 
 
 
 
 
 
 
Collaborative Colleagues:
David M. Nicol: colleagues
Jason Liu: colleagues
Michael Liljenstam: colleagues
Guanhua Yan: colleagues