Polynomial Time Algorithms for Stochastic Petri Net Analysis

本研究将为随机Petri网的高效、精确分析提供新的方法。该方法将为分布式和并行计算机系统的现实模型提供性能评估，目前没有仿真是不可能的。本研究结果将为随机Petri网模型的有效评估提供算法。这些算法的计算复杂度类似于排队网络模型的乘积形式技术。理论框架的适用性评估将使用一个原型设计系统SPAN来完成，该系统已经在开发中。一个相对年轻的研究者正在研究随机Petri网模型。如果成功的话，这项研究将有助于改进建模和理解分布式和并行计算。建议使用Support。

This research will develop new analytical techniques for Stochastic Petri Nets which are both efficient and exact. The methodology will provide performance evaluation for realistic models of distributed and parallel computer systems which is not currently possible without simulation. The results of this research will provide algorithms for the efficient evaluation of Stochastic Petri Net models. These algorithms have a computational complexity similar to the product form techniques for queuing network models. Evaluation of the applicability of the theoretical framework will be accomplished using a prototype design system, SPAN, which is already under development. Justification and Recommendation A relatively young investigator is studying Stochastic Petri Net models. If successful the research could lead to improved modelling and understanding distributed and parallel computations. Support is recommended.