By Topic

Stochastic Continuous Petri Nets: An Approximation of Markovian Net Models

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Vazquez, C.R. ; Dept. de Inf. e Ing. de Sist., Univ. de Zaragoza, Zaragoza, Spain ; Silva, M.

Fluidization constitutes a relaxation technique to study discrete event systems through a continuous approximated model, thus overcoming the state explosion problem. In this paper, the approximation of the average marking of Markovian Petri nets by the marking of the corresponding timed continuous Petri nets, under infinite-server semantics, is studied. This represents a sort of legitimization for the use of a continuous Petri net as a relaxation of a discrete Petri net. The main contribution is the addition of Gaussian noise in order to improve the approximation when the number of active servers (enabling degree) is large. The improvement is more evident when the system evolves “close” to the boundary of regions. In such a case, not only the expected value but also the probability distribution function of the marking may be approximated.

Published in:

Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on  (Volume:42 ,  Issue: 3 )