A bi-level Bernoulli scheme for database sampling
Peter J. Haas, Christian König
SIGMOD 2004
Generalized semi-Markov processes and stochastic Petri nets have been proposed as general frameworks for a discrete event simulation on a countable state space. The two formal systems differ, however, with respect to the clock setting (event scheduling) mechanism, the state transition mechanism, and the form of the state space. We obtain conditions under which the marking process of a stochastic Petri net “mimics” a generalized semi-Markov process in the sense that the two processes (and their underlying general state-space Markov chains) have the same finite dimensional distributions. The results imply that stochastic Petri nets have at least the modeling power of generalized semi-Markov processes for discrete event simulation. © 1988, Cambridge University Press. All rights reserved.
Peter J. Haas, Christian König
SIGMOD 2004
Peter J. Haas
Communications in Statistics. Part C: Stochastic Models
Byung-Kwon Choi, Tajhal Dayaram, et al.
PNAS
Rainer Gemulla, Wolfgang Lehner, et al.
VLDB Journal