The Experts below are selected from a list of 313149 Experts worldwide ranked by ideXlab platform
Eitan Altman - One of the best experts on this subject based on the ideXlab platform.
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Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy
IEEE Transactions on Vehicular Technology, 2013Co-Authors: Jocelyne Elias, Fabio Martignon, Lin Chen, Eitan AltmanAbstract:This paper addresses the joint pricing and network selection problem in cognitive radio networks. The problem is formulated as a Stackelberg game where first the Primary and Secondary operators set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service, or use a cheaper, best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash Equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop Equilibrium is reached by users in the network selection game, since in our model a large number of users must determine individually the network they should connect to. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of cognitive radio Systems.
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joint operator pricing and network selection game in cognitive radio networks Equilibrium System dynamics and price of anarchy
IEEE Transactions on Vehicular Technology, 2013Co-Authors: Jocelyne Elias, Fabio Martignon, Lin Chen, Eitan AltmanAbstract:This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash Equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop Equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR Systems.
Nan-jing Huang - One of the best experts on this subject based on the ideXlab platform.
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Dynamic Traffic Network Equilibrium System
Fixed Point Theory and Applications, 2010Co-Authors: Nan-jing HuangAbstract:We discuss the dynamic traffic network Equilibrium System problem. We introduce the Equilibrium definition based on Wardrop's principles when there are some internal relationships between different kinds of goods which transported through the same traffic network. Moreover, we also prove that the Equilibrium conditions of this problem can be equivalently expressed as a System of evolutionary variational inequalities. By using the fixed point theory and projected dynamic System theory, we get the existence and uniqueness of the solution for this Equilibrium problem. Finally, a numerical example is given to illustrate our results.
Jocelyne Elias - One of the best experts on this subject based on the ideXlab platform.
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Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy
IEEE Transactions on Vehicular Technology, 2013Co-Authors: Jocelyne Elias, Fabio Martignon, Lin Chen, Eitan AltmanAbstract:This paper addresses the joint pricing and network selection problem in cognitive radio networks. The problem is formulated as a Stackelberg game where first the Primary and Secondary operators set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service, or use a cheaper, best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash Equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop Equilibrium is reached by users in the network selection game, since in our model a large number of users must determine individually the network they should connect to. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of cognitive radio Systems.
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joint operator pricing and network selection game in cognitive radio networks Equilibrium System dynamics and price of anarchy
IEEE Transactions on Vehicular Technology, 2013Co-Authors: Jocelyne Elias, Fabio Martignon, Lin Chen, Eitan AltmanAbstract:This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash Equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop Equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR Systems.
Carlos F Daganzo - One of the best experts on this subject based on the ideXlab platform.
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morning commute with competing modes and distributed demand user Equilibrium System optimum and pricing
Transportation Research Part B-methodological, 2012Co-Authors: Eric J Gonzales, Carlos F DaganzoAbstract:The morning commute problem for a single bottleneck is extended to model mode choice in an urban area with time-dependent demand. This extension recognizes that street space is shared by cars and public transit. It is assumed that transit is operated independently of traffic conditions, and that when it is operated it consumes a fixed amount of space. As a first step, a single fixed-capacity bottleneck that can serve both cars and transit is studied. Commuters choose which mode to use and when to travel in order to minimize the generalized cost of their own trip. The transit agency chooses the headway and when to operate. Transit operations reduce the bottleneck’s capacity for cars by a fixed amount. The following results are shown for this type of bottleneck: 1. If the transit agency charges a fixed fare and operates at a given headway, and only when there is demand, then there is a unique user Equilibrium. 2. If the transit agency chooses its headway and time of operation for the common good, then there is a unique System optimum. 3. Time-dependent prices exist to achieve System optimum. Finally, it is also shown that results 2 and 3 apply to urban networks.
Fabio Martignon - One of the best experts on this subject based on the ideXlab platform.
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Joint Operator Pricing and Network Selection Game in Cognitive Radio Networks: Equilibrium, System Dynamics and Price of Anarchy
IEEE Transactions on Vehicular Technology, 2013Co-Authors: Jocelyne Elias, Fabio Martignon, Lin Chen, Eitan AltmanAbstract:This paper addresses the joint pricing and network selection problem in cognitive radio networks. The problem is formulated as a Stackelberg game where first the Primary and Secondary operators set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service, or use a cheaper, best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash Equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop Equilibrium is reached by users in the network selection game, since in our model a large number of users must determine individually the network they should connect to. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of cognitive radio Systems.
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joint operator pricing and network selection game in cognitive radio networks Equilibrium System dynamics and price of anarchy
IEEE Transactions on Vehicular Technology, 2013Co-Authors: Jocelyne Elias, Fabio Martignon, Lin Chen, Eitan AltmanAbstract:This paper addresses the joint pricing and network selection problem in cognitive radio networks (CRNs). The problem is formulated as a Stackelberg game, where the primary and secondary operators (POs and SOs) first set the network subscription price to maximize their revenue. Then, users perform the network selection process, deciding whether to pay more for a guaranteed service or to use a cheaper best-effort secondary network, where congestion and low throughput may be experienced. We derive optimal stable price and network selection settings. More specifically, we use the Nash Equilibrium concept to characterize the equilibria for the price setting game. On the other hand, a Wardrop Equilibrium is reached by users in the network selection game since, in our model, a large number of users must individually determine the network to which they should connect. Furthermore, we study network users' dynamics using a population game model, and we determine its convergence properties under replicator dynamics, which is a simple yet effective selection strategy. Numerical results demonstrate that our game model captures the main factors behind cognitive network pricing and network selection, thus representing a promising framework for the design and understanding of CR Systems.