{"title":"利用有效和解耦带宽快速模拟队列网络中的问题","authors":"M. Falkner, M. Devetsiklotis, I. Larnbadaris","doi":"10.1109/HPCS.1997.864035","DOIUrl":null,"url":null,"abstract":"A significant difficulty arising when using Monte Carlo (MC) simulation for the performance-analysis of communication networks is the long run times required to obtain accurate statistical estimates. Under the proper conditions, Importance Sampling (IS) is a technique that can speed up simulations involving rare events in network (queueing) systems [1, 2, 3, 4, 5]. Large speed-up factors in simulation run time can be obtained by using IS if the modification or bias of the underlying probability measures of certain random processes is carefully chosen. Fast simulation methods based on Large Deviation Theory [1, 3] have been successfully applied in many cases (recently, most notably in [51].","PeriodicalId":178651,"journal":{"name":"The Fourth IEEE Workshop on High-Performance Communication Systems","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Issues in fast simulation of networks of queues by use of effective and decoupling bandwidths\",\"authors\":\"M. Falkner, M. Devetsiklotis, I. Larnbadaris\",\"doi\":\"10.1109/HPCS.1997.864035\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A significant difficulty arising when using Monte Carlo (MC) simulation for the performance-analysis of communication networks is the long run times required to obtain accurate statistical estimates. Under the proper conditions, Importance Sampling (IS) is a technique that can speed up simulations involving rare events in network (queueing) systems [1, 2, 3, 4, 5]. Large speed-up factors in simulation run time can be obtained by using IS if the modification or bias of the underlying probability measures of certain random processes is carefully chosen. Fast simulation methods based on Large Deviation Theory [1, 3] have been successfully applied in many cases (recently, most notably in [51].\",\"PeriodicalId\":178651,\"journal\":{\"name\":\"The Fourth IEEE Workshop on High-Performance Communication Systems\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Fourth IEEE Workshop on High-Performance Communication Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPCS.1997.864035\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Fourth IEEE Workshop on High-Performance Communication Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCS.1997.864035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Issues in fast simulation of networks of queues by use of effective and decoupling bandwidths
A significant difficulty arising when using Monte Carlo (MC) simulation for the performance-analysis of communication networks is the long run times required to obtain accurate statistical estimates. Under the proper conditions, Importance Sampling (IS) is a technique that can speed up simulations involving rare events in network (queueing) systems [1, 2, 3, 4, 5]. Large speed-up factors in simulation run time can be obtained by using IS if the modification or bias of the underlying probability measures of certain random processes is carefully chosen. Fast simulation methods based on Large Deviation Theory [1, 3] have been successfully applied in many cases (recently, most notably in [51].