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ATM admission models of stochastic high level Petri nets based on hierarchical modeling

机译:基于等级建模的随机高水平培养网的ATM入学模型

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This paper presents a framework for modeling and analyzing ATM admission control using Stochastic High Level Petri Net (SHLPN). SHLPN is chosen because it is a powerful graphical and mathematical modeling tool that is able to handle concurrent, asynchronous, nondeterministic and stochastic events. In addition, there exists a set of well-developed performance analysis techniques for SHLPN. This paper uses a hierarchical modeling technique to specify complex ATM network mechanisms using a top-down approach. However, in analyzing the performance of the network, a bottom-up approach is adopted. To tackle the state space explosion problem, a SHLPN model is decomposed into submodels. These subnets are independently evaluated with all possible population which are then substituted by transitions with approximate equivalent performance in the original model. The technique is illustrated by modeling and evaluating a specific connection admission control policy.
机译:本文介绍了使用随机高水平Petri网(SHLPN)建模和分析ATM准入控制的框架。选择了SHLPN,因为它是一种功能强大的图形和数学建模工具,可以处理并发,异步,非季度和随机事件。此外,还存在一组用于SHLPN的良好开发的性能分析技术。本文使用分层建模技术使用自上而下的方法来指定复杂的ATM网络机制。但是,在分析网络性能时,采用自下而上的方法。为了解决状态空间爆炸问题,SHLPN模型被分解为子模型。这些子网被独立地评估了所有可能的群体,然后通过在原始模型中的近似等同性能的转换来代替。通过建模和评估特定的连接录取控制策略来说明该技术。

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