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On some modeling issues in high speed networks
Communication networks have experienced tremendous growth in recent years, and it has become ever more challenging to design, control and manage systems of such speed, size and complexity. The traditional performance modeling tools include analysis, discrete-event simulation and network emulation.^ In this dissertation, we propose a new approach for performance modeling and we call it time-driven fluid simulation. Time-driven fluid simulation is a technique based on modeling the traffic going through the network as continuous fluid flows and the network nodes as fluid servers. Time is discretized into fixed-length intervals and the system is simulated by recursively computing the system state and advance the simulation clock. When the interval length is large, each chunk of fluid processed within one interval may represent thousands of packets/cells. In addition, since the simulation is synchronized by the fixed time intervals, it is easy to parallelize the simulator. These two factors enable us to tremendously speed up the simulation.^ For single class fluid with probability routing, we prove that the error introduced by discretizing a fluid model is within a deterministic bound proportional to the discretization interval length and is not related to the network size. For multi-class traffic passing through FIFO servers with class-based routing, we prove that the worst case discretization error for any fluid flow may grow linearly with the number of hops the flow passes but unaffected by the overall network size and the discretization error of other classes. We further show via simulation that certain performance measures are in fact quite robust with respect to the discretization interval length and the path length of the flow (in number of hops), and the discretization error is much smaller than that given by the worst case bound. These results show that fluid simulation can be a useful performance modeling tool filling the gap between discrete-event simulation and analysis.^ In this dissertation, we also apply another technique, rational approximation, to estimate the cell loss probabilities for an ATM multiplexer fed by a self-similar process. This is another method that compensates the analysis and simulation techniques. ^
Engineering, Electronics and Electrical|Engineering, System Science|Computer Science
"On some modeling issues in high speed networks"
(January 1, 1998).
Electronic Doctoral Dissertations for UMass Amherst.