Pricing in computer networks: motivation, formulation, and example
IEEE/ACM Transactions on Networking (TON)
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ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
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ISCC '04 Proceedings of the Ninth International Symposium on Computers and Communications 2004 Volume 2 (ISCC"04) - Volume 02
Pricing network resources for adaptive applications
IEEE/ACM Transactions on Networking (TON)
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ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
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ICDCSW '06 Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems
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IEEE/ACM Transactions on Networking (TON)
On the feasibility of dynamic congestion-based pricing in differentiated services networks
IEEE/ACM Transactions on Networking (TON)
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IEEE Communications Magazine
Capacity of ad hoc wireless networks with infrastructure support
IEEE Journal on Selected Areas in Communications
Congestion-based pricing resource management in broadband wireless networks
IEEE Transactions on Wireless Communications
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In this paper, we model a market-based cognitive radio network where multiple wireless service providers (WSPs) offer competitive prices to users. We assume that WSPs use a mix of access technologies to provide a wide variety of wireless services (e.g., voice, data etc.) with a certain level of QoS while maximizing their revenues. Using a non-cooperative game model, we propose differentiated pricing strategies for the WSPs and users. We also propose an optimal strategy for access network selection by the service providers which minimizes the effect on QoS of the existing users and increases self-coexistence. We show that, in order to achieve Nash equilibrium, it is in the best interest of both WSPs and users to adhere to the proposed strategies. Performance issues from both providers' and users' perspectives are studied through analytical computations and simulation experiments. Analysis shows that our proposed pricing policy represents the oligopoly market, i.e., exhibiting larger sensitivity to a new provider when the number of existing providers is low and lower sensitivity when the number of existing providers is high. Simulation results demonstrate that the proposed pricing and network selection policies benefit both users and WSPs.