Theory of Modeling and Simulation
Theory of Modeling and Simulation
SIAM Journal on Scientific Computing
Quantized-state systems: a DEVS Approach for continuous system simulation
Transactions of the Society for Computer Simulation International - Recent advances in DEVS Methodology--part I
Multi-adaptive time integration
Applied Numerical Mathematics - Special issue: Workshop on innovative time integrators for PDEs
Parallel discrete event simulation with application to continuous systems
Parallel discrete event simulation with application to continuous systems
A discrete event method for wave simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
A Second Order Accurate Adams-Bashforth Type Discrete Event Integration Scheme
Proceedings of the 21st International Workshop on Principles of Advanced and Distributed Simulation
Proceedings of the 21st International Workshop on Principles of Advanced and Distributed Simulation
On the stability and performance of discrete event methods for simulating continuous systems
Journal of Computational Physics
Multilevel methodology for simulation of spatio-temporal systems with heterogeneous activity: application to spread of valley fever fungus
Discrete event solution of gas dynamics within the DEVS framework
ICCS'03 Proceedings of the 2003 international conference on Computational science
Proceedings of the Winter Simulation Conference
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From a modeling and simulation perspective, studying dynamic systems consists of focusing on changes in states. According to the precision of state changes, generic algorithms can be developed to track the activity of sub-systems. This paper aims at describing and applying this more natural and intuitive way to describe and implement dynamic systems. Activity is defined mathematically. A generic application case of diffusion is experimented with to compare the efficiency of quantized state methods using this new approach with traditional methods which do not focus computations on active areas. Our goal is to demonstrate that the concept of activity can estimate the computational effort required by a quantized state method. Specifically, when properly designed, a discrete-event simulator for such a method achieves a reduction in the number of state transitions that more than compensates for the overhead it imposes.