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A Simulation Engine for Stochastic Timed Petri Nets and Application to Emergency Healthcare Systems

机译:随机定时Petri网的仿真引擎及其在应急医疗系统中的应用

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摘要

In many service delivery systems, the quantity of available resources is often a decisive factor of service quality. Re-sources can be personnel, offices, devices, supplies, and so on, de-pending on the nature of the services a system provides. Al-though service computing has been an active research topic for decades, general approaches that assess the impact of resource provisioning on service quality matrices in a rigorous way re-main to be seen. Petri nets have been a popular formalism for modeling systems exhibiting behaviors of competition and con-currency for almost a half century. Stochastic timed Petri nets (STPN), an extension to regular Petri nets, are a powerful tool for system performance evaluation. However, we did not find any single existing STPN software tool that supports all timed trans-ition firing policies and server types, not to mention resource pro-visioning and requirement analysis. This paper presents a generic and resource oriented STPN simulation engine that provides all critical features necessary for the analysis of service delivery sys-tem quality vs. resource provisioning. The power of the simula-tion system is illustrated by an application to emergency health care systems.
机译:在许多服务交付系统中,可用资源的数量通常是服务质量的决定性因素。资源可以是人员,办公室,设备,耗材等,这取决于系统提供的服务的性质。尽管服务计算一直是活跃的研究主题,但以严格的方式评估资源配置对服务质量矩阵的影响的通用方法仍然有待观察。 Petri网一直是流行的形式化建模系统,这种系统展现了竞争和并发的行为近半个世纪。随机定时Petri网(STPN)是常规Petri网的扩展,是系统性能评估的强大工具。但是,我们没有找到任何支持所有定时过渡触发策略和服务器类型的现有STPN软件工具,更不用说资源配置和需求分析了。本文介绍了一种通用的面向资源的STPN仿真引擎,该引擎提供了分析服务交付系统质量与资源供应之间必需的所有关键功能。仿真系统的功能通过在紧急医疗系统中的应用来说明。

著录项

  • 来源
    《自动化学报(英文版)》 |2019年第4期|969-980|共12页
  • 作者单位

    Monmouth University, New Jersey 07764-1898 USA;

    Monmouth University, New Jersey 07764-1898 USA;

    School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China;

  • 收录信息 中国科学引文数据库(CSCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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  • 入库时间 2022-08-19 04:29:05
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