{"title":"有限排队网络完美模拟的Psi^2软件工具","authors":"J. Vincent, Jérôme Vienne","doi":"10.1109/QEST.2007.37","DOIUrl":null,"url":null,"abstract":"Markovian networks of finite capacity queues are widely used models for performance evaluation of systems and networks. Unfortunately, excepted in some specific situations, these models are not tractable analytically. Perfect simulation provides a new technique to sample steady-state and avoids the burn-in time period. When the simulation algorithm stops, the returned state value is in steady-state. We applied this technique first to Markov chain with sparse transition matrix, and to queueing networks with finite capacities and complex routing strategies. The sofware have been developed to validate this simulation approach and applied to in the context of low probability events estimation. The design of the software architecture is presented.","PeriodicalId":249627,"journal":{"name":"Fourth International Conference on the Quantitative Evaluation of Systems (QEST 2007)","volume":"29 7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Psi^2 a Software Tool for the Perfect Simulation of Finite Queueing Networks\",\"authors\":\"J. Vincent, Jérôme Vienne\",\"doi\":\"10.1109/QEST.2007.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Markovian networks of finite capacity queues are widely used models for performance evaluation of systems and networks. Unfortunately, excepted in some specific situations, these models are not tractable analytically. Perfect simulation provides a new technique to sample steady-state and avoids the burn-in time period. When the simulation algorithm stops, the returned state value is in steady-state. We applied this technique first to Markov chain with sparse transition matrix, and to queueing networks with finite capacities and complex routing strategies. The sofware have been developed to validate this simulation approach and applied to in the context of low probability events estimation. The design of the software architecture is presented.\",\"PeriodicalId\":249627,\"journal\":{\"name\":\"Fourth International Conference on the Quantitative Evaluation of Systems (QEST 2007)\",\"volume\":\"29 7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fourth International Conference on the Quantitative Evaluation of Systems (QEST 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/QEST.2007.37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fourth International Conference on the Quantitative Evaluation of Systems (QEST 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QEST.2007.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Psi^2 a Software Tool for the Perfect Simulation of Finite Queueing Networks
Markovian networks of finite capacity queues are widely used models for performance evaluation of systems and networks. Unfortunately, excepted in some specific situations, these models are not tractable analytically. Perfect simulation provides a new technique to sample steady-state and avoids the burn-in time period. When the simulation algorithm stops, the returned state value is in steady-state. We applied this technique first to Markov chain with sparse transition matrix, and to queueing networks with finite capacities and complex routing strategies. The sofware have been developed to validate this simulation approach and applied to in the context of low probability events estimation. The design of the software architecture is presented.