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9.1. Introduction One of the main interests of Petri nets is to combine qualitative analysis (i.e. property veri cation) and quantitative analysis (i.e. performance evaluation) [FLO 78, MOL 81, REI 98a, REI 98b]. In comparison, concurrency models such as process algebra [HIL 96] have only recently been extended with stochastic features, and although rst results are promising, there is still more research to be done on performance evaluation of stochastic Petri nets. Similarly, the usual models for performance evaluation, such as queueing networks [KLE 75], do not include synchronization mechanisms and adding them using ad hoc constructions [FDI 86, DAL 97] does not achieve the generality and the simplicity of concurrency modeling with Petri nets. Stochastic Petri nets were introduced in a pragmatic way at the end of the 1970s, in order to bene t from Markov chain evaluation methods. This approach leads to immediate results but conceals the semantic features underlying the de nition of stochastic Petri nets and cannot be easily generalized to different probability distributions. So in the three chapters devoted to stochastic Petri nets, we proceed as follows. First we tackle the semantic level, i.e. the level of the stochastic processes, and we study their properties with the aim of designing analysis methods. Here we have chosen to emphasize the principles which characterize every method. So, we omit programming features related to numerical computations. Indeed, these features are not speci c to stochastic Petri nets and are covered by a number of excellent books [STE 94, BOL 98]. Then we present models (and extensions) of stochastic java code 128 reader Barcode Reader . Free Online Web Application
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