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Simulating the Time-Scale Dynamics of Network Traffic Using Homogeneous Modeling
Published
Author(s)
Kevin L. Mills, J Yuan
Abstract
Simulating and understanding traffic dynamics in large networks present difficult challenges due to the complexity of such networks, coupled with limitations inherent in simulation modeling. Typically, simulation models used to study traffic dynamics include substantial detail representing protocol mechanisms across several layers of functionality. Such models must be restricted in space and time in order to prove computationally tractable. We propose an alternate approach that uses homogeneous modeling, coupled with an increased level of abstraction, in order to explore networks at larger space-time scales than might otherwise prove feasible. We believe such models might help to develop intuition and insight about the space-time dynamics of large networks. To illustrate the potential promise of our approach, we examine some current understandings of the timescale dynamics of network traffic, and we discuss some speculative results obtained with our homogeneous modeling approach. Using a wavelet-based technique, we show various correlation structures, and changes in correlation structures, of network traffic under effects of traffic sources, transport mechanisms, and network structure. Our simulation results encourage further investigation of our approach, which might benefit from cross-verifications against more detailed simulation models.
Mills, K.
and Yuan, J.
(2006),
Simulating the Time-Scale Dynamics of Network Traffic Using Homogeneous Modeling, Journal of Research (NIST JRES), National Institute of Standards and Technology, Gaithersburg, MD
(Accessed November 7, 2024)