{"title":"下一代网络服务的定价与资源优化配置","authors":"M. Kallitsis, G. Michailidis, M. Devetsikiotis","doi":"10.1109/SARNOF.2007.4567398","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce a pricing model that ensures efficient resource allocation that provides guaranteed quality of service while maximizing profit in multiservice networks. Specifically, a dynamic allocation policy is examined that relies on online measurements while each service class operates under a probabilistic bound delay constraint. We present a rigorous analysis of the properties of the policy that provides insights into its workings as well as its sensitivity to various parameters. Finally, its performance is evaluated through an extensive numerical study.","PeriodicalId":293243,"journal":{"name":"2007 IEEE Sarnoff Symposium","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Pricing and optimal resource allocation in next generation network services\",\"authors\":\"M. Kallitsis, G. Michailidis, M. Devetsikiotis\",\"doi\":\"10.1109/SARNOF.2007.4567398\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce a pricing model that ensures efficient resource allocation that provides guaranteed quality of service while maximizing profit in multiservice networks. Specifically, a dynamic allocation policy is examined that relies on online measurements while each service class operates under a probabilistic bound delay constraint. We present a rigorous analysis of the properties of the policy that provides insights into its workings as well as its sensitivity to various parameters. Finally, its performance is evaluated through an extensive numerical study.\",\"PeriodicalId\":293243,\"journal\":{\"name\":\"2007 IEEE Sarnoff Symposium\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE Sarnoff Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SARNOF.2007.4567398\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE Sarnoff Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SARNOF.2007.4567398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pricing and optimal resource allocation in next generation network services
In this paper, we introduce a pricing model that ensures efficient resource allocation that provides guaranteed quality of service while maximizing profit in multiservice networks. Specifically, a dynamic allocation policy is examined that relies on online measurements while each service class operates under a probabilistic bound delay constraint. We present a rigorous analysis of the properties of the policy that provides insights into its workings as well as its sensitivity to various parameters. Finally, its performance is evaluated through an extensive numerical study.