Enabling Theoretical Model Based Techniques for Simulating Large Scale Networks
Kim, Hwangnam
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Permalink
https://hdl.handle.net/2142/81656
Description
Title
Enabling Theoretical Model Based Techniques for Simulating Large Scale Networks
Author(s)
Kim, Hwangnam
Issue Date
2004
Doctoral Committee Chair(s)
Jennifer C. Hou
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Language
eng
Abstract
We develop a fluid model of describing the data transmission activities in IEEE 802.11-operated WLANs, and used it to explore whether or not fluid model-based simulation is effective in simulating WLANs. Fluid model based simulation is not well-suited for studying the network behavior under light and/or sporadic traffic, as it assumes a large number of flows in networks. To address the issue, we introduce the notion of network calculus based simulation; we characterize the interaction between TCP and AQM, determine necessary scheduling rules to regulate TCP traffic, and incorporate the rules into a simulation engine. Although both fluid model based and network calculus based simulation give encouraging results in terms of the execution time, they cannot provide packet level details, such as the instantaneous queue length and packet dropping probability, due to the use of larger simulation units. In order to provide the packet level dynamics, we propose mixed mode simulation. In mixed mode simulation, packet mode simulation co-exists with theoretical model-based simulation within one simulation framework. We also propose a new rescaling simulation methodology (RSM) to simulate IP networks with TCP and/or UDP traffic for the cases that the behaviors of all the flows should be inspected. The underlying idea of RSM based simulation is to reduce the computation by scaling down the network to one that can be simulated in a short time to produce sufficient results, and then to extrapolate the results for the original network with the results obtained from the smaller network.
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