TY - JOUR
T1 - The Activity-tracking paradigm in discrete-event modeling and simulation
T2 - The case of spatially continuous distributed systems
AU - Muzy, Alexandre
AU - Jammalamadaka, Rajanikanth
AU - Zeigler, Bernard P.
AU - Nutaro, james J.
PY - 2011/5
Y1 - 2011/5
N2 - 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.
AB - 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.
KW - activity-tracking paradigm
KW - diffusion process
KW - discrete-event modeling and simulation
KW - quantization
UR - http://www.scopus.com/inward/record.url?scp=79954495888&partnerID=8YFLogxK
U2 - 10.1177/0037549710365155
DO - 10.1177/0037549710365155
M3 - Article
AN - SCOPUS:79954495888
SN - 0037-5497
VL - 87
SP - 449
EP - 464
JO - SIMULATION
JF - SIMULATION
IS - 5
ER -