{"title":"基于博弈论和前景理论的用户偏好感知无线通信多媒体定价模型","authors":"K. Ramamoorthy","doi":"10.1109/ASE.2019.00157","DOIUrl":null,"url":null,"abstract":"Providing user satisfaction is a major concern for on-demand multimedia service providers and Internet carriers in Wireless Communications. Traditionally, user satisfaction was measured objectively in terms of throughput and latency. Nowadays the user satisfaction is measured using subjective metrices such as Quality of Experience (QoE). Recently, Smart Media Pricing (SMP) was conceptualized to price the QoE rather than the binary data traffic in multimedia services. In this research, we have leveraged the SMP concept to chalk up a QoE-sensitive multimedia pricing framework to allot price, based on the user preference and multimedia quality achieved by the customer. We begin by defining the utility equations for the provider-carrier and the customer. Then we translate the profit maximizing interplay between the parties into a two-stage Stackelberg game. We model the user personal preference using Prelec weighting function which follows the postulates Prospect Theory (PT). An algorithm has been developed to implement the proposed pricing scheme and determine the Nash Equilibrium. Finally, the proposed smart pricing scheme was tested against the traditional pricing method and simulation results indicate a significant boost in the utility achieved by the mobile customers.","PeriodicalId":378594,"journal":{"name":"Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"User preference aware multimedia pricing model using game theory and prospect theory for wireless communications\",\"authors\":\"K. Ramamoorthy\",\"doi\":\"10.1109/ASE.2019.00157\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Providing user satisfaction is a major concern for on-demand multimedia service providers and Internet carriers in Wireless Communications. Traditionally, user satisfaction was measured objectively in terms of throughput and latency. Nowadays the user satisfaction is measured using subjective metrices such as Quality of Experience (QoE). Recently, Smart Media Pricing (SMP) was conceptualized to price the QoE rather than the binary data traffic in multimedia services. In this research, we have leveraged the SMP concept to chalk up a QoE-sensitive multimedia pricing framework to allot price, based on the user preference and multimedia quality achieved by the customer. We begin by defining the utility equations for the provider-carrier and the customer. Then we translate the profit maximizing interplay between the parties into a two-stage Stackelberg game. We model the user personal preference using Prelec weighting function which follows the postulates Prospect Theory (PT). An algorithm has been developed to implement the proposed pricing scheme and determine the Nash Equilibrium. Finally, the proposed smart pricing scheme was tested against the traditional pricing method and simulation results indicate a significant boost in the utility achieved by the mobile customers.\",\"PeriodicalId\":378594,\"journal\":{\"name\":\"Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering\",\"volume\":\"106 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASE.2019.00157\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASE.2019.00157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
提供用户满意度是无线通信中按需多媒体服务提供商和互联网运营商关注的主要问题。传统上,用户满意度是根据吞吐量和延迟来客观衡量的。目前,用户满意度是用主观指标来衡量的,如体验质量(QoE)。最近,智能媒体定价(Smart Media Pricing, SMP)的概念是对多媒体服务中的QoE而不是二进制数据流量进行定价。在这项研究中,我们利用SMP概念,根据用户偏好和客户获得的多媒体质量,建立了一个对质量质量敏感的多媒体定价框架来分配价格。我们首先定义供应商-运营商和客户的效用方程。然后,我们将各方之间的利益最大化相互作用转化为两阶段的Stackelberg博弈。我们使用Prelec加权函数来建立用户个人偏好模型,该函数遵循预期理论(PT)的假设。本文开发了一种算法来实现所提出的定价方案并确定纳什均衡。最后,对所提出的智能定价方案与传统定价方法进行了测试,仿真结果表明,移动客户实现的效用显著提高。
User preference aware multimedia pricing model using game theory and prospect theory for wireless communications
Providing user satisfaction is a major concern for on-demand multimedia service providers and Internet carriers in Wireless Communications. Traditionally, user satisfaction was measured objectively in terms of throughput and latency. Nowadays the user satisfaction is measured using subjective metrices such as Quality of Experience (QoE). Recently, Smart Media Pricing (SMP) was conceptualized to price the QoE rather than the binary data traffic in multimedia services. In this research, we have leveraged the SMP concept to chalk up a QoE-sensitive multimedia pricing framework to allot price, based on the user preference and multimedia quality achieved by the customer. We begin by defining the utility equations for the provider-carrier and the customer. Then we translate the profit maximizing interplay between the parties into a two-stage Stackelberg game. We model the user personal preference using Prelec weighting function which follows the postulates Prospect Theory (PT). An algorithm has been developed to implement the proposed pricing scheme and determine the Nash Equilibrium. Finally, the proposed smart pricing scheme was tested against the traditional pricing method and simulation results indicate a significant boost in the utility achieved by the mobile customers.