Ayan Paul, S. Mandal, M. Maitra, S. Sadhukhan, U. Tiwari, V. Agrawal
{"title":"A dynamic agreement framework for trading of wireless services","authors":"Ayan Paul, S. Mandal, M. Maitra, S. Sadhukhan, U. Tiwari, V. Agrawal","doi":"10.1109/ANTS.2012.6524230","DOIUrl":null,"url":null,"abstract":"Today's rapid change in demands of wireless services is compelling wireless service providers (WSPs) to deploy most recent wireless technologies (such as 3G, LTE) in the market. In India, there are many WSPs that hold only 2G license in a particular service area. Naturally, their business prospect is affected as they cannot provide the cutting edge services. In this work, we have suggested an efficient strategy for these WSPs to enable them to provide new age services to their own customers. We envisage a scenario where, unlicensed WSP provides services to its users by buying bulk services from any licensed WSP. In reality, similar kind of arrangement exists where some WSPs collaborate with each other by entering into a long term static agreement. However, in this work, we have proposed an agent based dynamic agreement framework as an alternative solution. In our model, agents of the licensed and unlicensed WSPs try to reach an agreement for short term by negotiating on different service attributes (such as bandwidth, quality of service, price and credit limit etc.) of any particular service e.g. high speed internet (HSI). Initially, we have proved the existence of Nash equilibrium where, utilities of both buyer and seller maximize in case of HSI service. Subsequently, we have presented a novel genetic algorithm (GA) based negotiation mechanism for the agents. We have chosen joint utility of buyer and seller as the performance measure of our trading mechanism. Our simulation result shows that our negotiation mechanism provides better joint utility compared to the current static agreement strategy.","PeriodicalId":340711,"journal":{"name":"2012 IEEE International Conference on Advanced Networks and Telecommunciations Systems (ANTS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Advanced Networks and Telecommunciations Systems (ANTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANTS.2012.6524230","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Today's rapid change in demands of wireless services is compelling wireless service providers (WSPs) to deploy most recent wireless technologies (such as 3G, LTE) in the market. In India, there are many WSPs that hold only 2G license in a particular service area. Naturally, their business prospect is affected as they cannot provide the cutting edge services. In this work, we have suggested an efficient strategy for these WSPs to enable them to provide new age services to their own customers. We envisage a scenario where, unlicensed WSP provides services to its users by buying bulk services from any licensed WSP. In reality, similar kind of arrangement exists where some WSPs collaborate with each other by entering into a long term static agreement. However, in this work, we have proposed an agent based dynamic agreement framework as an alternative solution. In our model, agents of the licensed and unlicensed WSPs try to reach an agreement for short term by negotiating on different service attributes (such as bandwidth, quality of service, price and credit limit etc.) of any particular service e.g. high speed internet (HSI). Initially, we have proved the existence of Nash equilibrium where, utilities of both buyer and seller maximize in case of HSI service. Subsequently, we have presented a novel genetic algorithm (GA) based negotiation mechanism for the agents. We have chosen joint utility of buyer and seller as the performance measure of our trading mechanism. Our simulation result shows that our negotiation mechanism provides better joint utility compared to the current static agreement strategy.