ANSS '04 Proceedings of the 37th annual symposium on Simulation
A flexible approach to multi-level agent-based simulation with the mesoscopic representation
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
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Abstract: Modeling and simulation of large, high resolution network models is a time consuming task even when parallel simulation techniques are employed. Processing voluminous, detailed simulation data further increases the complexity of analysis. Consequently, the models (or parts of the models) are abstracted to improve performance of the simulations by trading-off model details and fidelity. However, abstraction defeats the purpose of studying high resolution network models and magnifies the problems of validation! An alternative approach is to dynamically (i.e., during the course of simulation) change the resolution of the model (or parts of the model). In our component based Network Modeling and Simulation Framework (NMSF), we have enabled dynamic changes to the resolution of a model using a novel methodology called Dynamic Component Substitution (DCS). Using DCS, a set of components can be substituted by a functionally equivalent component (or vice versa) to change the resolution (or the level of abstraction) of a network model. DCS improves the overall efficiency of simulations through dynamic tradeoffs between resolution of a model, simulation performance, and analysis overheads. This paper presents an overview of DCS and the issues involved in enabling DCS in NMSF, an optimistically synchronized parallel simulation framework. The experiments conducted to evaluate the effectiveness of DCS are also illustrated. Our studies indicate that DCS provides an effective technique to considerably improve the overall efficiency of network simulations.