{"title":"Revenue Maximization for Communication Networks with Usage-Based Pricing","authors":"Shuqin Li, Jianwei Huang, S. Li","doi":"10.1109/GLOCOM.2009.5425338","DOIUrl":null,"url":null,"abstract":"We study the optimal usage-based pricing problem in a resource-bounded network with one profit-maximizing service provider and multiple groups of surplus-maximizing users. We first analytically derive the optimal pricing mechanism that the service provider maximizes the service provider's revenue under complete network information. Then we consider the incomplete information case, and propose two incentive compatible pricing schemes that achieve different complexity and performance tradeoff. Finally, by properly combining the two pricing schemes, we can show that it is possible to maintain a very small revenue loss (e.g., 0.5% in a two-group case) without knowing detailed information of each user in the network.","PeriodicalId":405624,"journal":{"name":"GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"84","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLOCOM.2009.5425338","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 84
Abstract
We study the optimal usage-based pricing problem in a resource-bounded network with one profit-maximizing service provider and multiple groups of surplus-maximizing users. We first analytically derive the optimal pricing mechanism that the service provider maximizes the service provider's revenue under complete network information. Then we consider the incomplete information case, and propose two incentive compatible pricing schemes that achieve different complexity and performance tradeoff. Finally, by properly combining the two pricing schemes, we can show that it is possible to maintain a very small revenue loss (e.g., 0.5% in a two-group case) without knowing detailed information of each user in the network.