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PNiQ: integration of queuing networks in generalised stochastic Petri nets

机译:PNiQ:排队网络在广义随机Petri网中的集成

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Generalised stochastic Petri nets (GSPNs) and queuing networks are combined at the modelling level by defining Petri nets including queuing networks (PNiQ). The definition is especially designed to allow approximate analysis by aggregation of the queuing networks and replacing them with GSPN elements. Usually the aggregation of combined GSPN and queuing network models is carried out manually, which limits the use of this technique to experts and furthermore may easily lead to modelling errors and larger approximation errors than are inherent in the method. These are avoided by the definition of PNiQ, which shows how to incorporate queuing networks into GSPNs and provides interfaces between them. This makes combined modelling easier and less error-prone. Steady-state analysis of the model can be carried out automatically: queuing network parts are analysed with efficient queuing network algorithms for large nets and are replaced by GSPN subnets that model the delay of tokens in the queuing network. The resulting GSPN can then be handled with state-of-the-art tools.
机译:通过定义包括排队网络(PNiQ)的Petri网,可以在建模级别将广义随机Petri网(GSPN)和排队网络结合起来。该定义经过特殊设计,可以通过排队网络的聚合并将其替换为GSPN元素来进行近似分析。通常,合并的GSPN和排队网络模型的汇总是手动进行的,这限制了该技术的使用,并且与该方法固有的相比,很容易导致建模误差和更大的近似误差。通过PNiQ的定义可以避免这些问题,该定义说明了如何将排队网络合并到GSPN中并提供它们之间的接口。这使得组合建模更加容易,并且不易出错。该模型的稳态分析可以自动进行:使用大型网络的有效排队网络算法对排队网络​​部分进行分析,并用GSPN子网代替,该模型对排队网络​​中令牌的延迟进行建模。然后可以使用最新的工具来处理生成的GSPN。

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