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Automated Customer-Centric Performance Analysis of Generalised Stochastic Petri Nets Using Tagged Tokens

机译:基于标记令牌的广义随机petri网自动客户中心性能分析

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摘要

Since tokens in Generalised Stochastic Petri Net (GSPN) models are indistinguishable, it is not always possible to reason about customer-centric performance measures. To remedy this, we propose tagged tokens - a variant of the tagged customer technique used in the analysis of queueing networks. Under this scheme, one token in a structurally restricted net is tagged and its position tracked as it moves around the net. Performance queries can then be phrased in terms of the position of the tagged token. To date, the tagging of customers or tokens has been a time-consuming, manual and model-specific process. By contrast, we present here a completely automated methodology for the tagged token analysis of GSPNs. We first describe an intuitive graphical means of specifying the desired tagging configuration, along with the constraints on GSPN structure which must be observed for tagged tokens to be incorporated. We then present the mappings required for automatically converting a GSPN with a user-specified tagging structure into a Coloured GSPN (CGSPN), and thence into an unfolded GSPN which can be analysed for performance measures of interest by existing tools. We further show how our methodology integrates with Performance Trees, a formalism for the specification of performance queries. We have implemented our approach in the open source PIPE Petri net tool, and use this to illustrate the extra expressibility granted by tagged tokens through the analysis of a GSPN model of a hospitals Accident and Emergency department. © 2009 Elsevier B.V. All rights reserved.
机译:由于广义随机Petri网(GSPN)模型中的令牌是无法区分的,因此并非总是可以推理出以客户为中心的绩效指标。为了解决这个问题,我们提出了标记令牌-排队网络分析中使用的标记客户技术的一种变体。在此方案下,对结构受限的网络中的一个令牌进行标记,并跟踪其在网络中移动时的位置。然后可以根据标记令牌的位置来表达性能查询。迄今为止,标记客户或令牌是一个耗时,手动和特定于模型的过程。相比之下,我们在这里介绍了一种用于GSPN的标记令牌分析的完全自动化的方法。我们首先描述一种指定所需标记配置的直观图形方式,以及对于要合并标记令牌必须遵守的GSPN结构约束。然后,我们介绍了将具有用户指定标记结构的GSPN自动转换为有色GSPN(CGSPN)所需的映射,然后将其转换为展开的GSPN,可以使用现有工具对其进行性能分析。我们进一步展示了我们的方法是如何与性能树(性能树的规范形式)集成的。我们已经在开源PIPE Petri网工具中实现了我们的方法,并通过对医院急诊科的GSPN模型进行分析,来说明标记的令牌所赋予的额外可表达性。 ©2009 Elsevier B.V.保留所有权利。

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    Knottenbelt W; Dingle N;

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