基于随机Petri网的系统性能评价

性能评价是计算机网络和计算机系统研究与应用的重要理论和支撑技术。综述了作者在基于随机 Petri网(SPN)的系统性能评价方面的研究工作 ,内容包括多服务器多队列网络、 SPN非乘积解系统的判定与界限求解、非乘积解系统模型的分解和近似求解、网络系统自相似业务到达、SPN模型的精化设计、含有非 Markov过程的排队 Petri网、基于 SPN的工作流系统、基于 SPN模型的缓冲优先调度策略、扩展时段时序逻辑的推理机制等方面。今后应加强对非Markov模型、综合模型及分解压缩技术等的研究

Performance evaluation of systems using stochastic Petri nets

Performance evaluation of computer networks is an important part of computer research and development. This paper summarizes the authors' research work on performance evaluation of systems using stochastic Petri nets (SPN). The researches include multiserver multiqueue networks, decisions in non product form solution systems and bounds solutions analyzed using stochastic Petri nets, decomposition and approximate solutions of non product form solutions, network systems with self similar arrivals, refinement of model structures for stochastic Petri nets, queuing Petri nets including non Markovian process, workflow systems based on stochastic Petri net models, buffer priority scheduling policies using stochastic Petri net models, and the inference engine of extended interval temporal logic. Further research will focus on non Markov models, integrated models, and decomposition and aggregation for SPN.