Large Scale Simulation of Manufacturing and Communications Systems

制造和通信系统的大规模仿真

• 批准号: 0085165
• 负责人: Shane Henderson
• 金额: $ 29.53万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-15 至 2001-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0085165&HistoricalAwards=false
• 关键词: Large; Scale; Simulation; Manufacturing; Communications

This grant provides funding for research on methods for performance evaluation of large network models of complex systems that arise in manufacturing and communication systems. The systems in mind are so complex that simulation is typically the only viable tool for benchmarking the system. Unfortunately, simulation is not a particularly scalable technology. The research focuses on developing fast and efficient simulation methods for complex systems, by exploiting prior knowledge of the system's dynamics. Such prior knowledge may be obtained from examination of a "fluid model", for example, which is an idealized model of complex systems where all entities are modeled as fluids flowing through pipes. A great deal is known about fluid models, and the hope is that this information can lead to very efficient simulation methods.If successful, the results of this research will ensure that simulation becomes a more scalable tool than before for a large class of systems. The central idea is that more accurate results may be obtained in (far) less time than would otherwise be the case. One can then implement more efficient algorithms for searching over different operating policies to determine the best operating policy, or at the very least one that is better than the existing policy.

这笔赠款用于研究制造和通信系统中出现的复杂系统的大型网络模型的性能评估方法。考虑到的系统是如此复杂，模拟通常是唯一可行的基准系统工具。不幸的是，模拟并不是一种特别可扩展的技术。研究的重点是通过利用系统动力学的先验知识，开发快速有效的复杂系统仿真方法。这样的先验知识可以通过检查例如是复杂系统的理想化模型的“流体模型”来获得，其中所有实体都被建模为流经管道的流体。人们对流体模型有很多了解，希望这些信息可以导致非常有效的模拟方法。如果成功，这项研究的结果将确保模拟成为一种比以前更具可扩展性的工具，适用于更大类别的系统。其核心思想是，与其他情况相比，可以在(远)短的时间内获得更准确的结果。然后，可以实现更高效的算法来搜索不同的操作策略以确定最佳操作策略，或者至少确定比现有策略更好的操作策略。