Incentive-Based Pricing for Network Games with Complete and Incomplete Information

Shen, Hongxia; Başar, Tamer

doi:10.1007/978-0-8176-4553-3_22

Cited by 31 publications

(35 citation statements)

References 11 publications

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“…Problems of pricing to maximize revenue are considered in [11] [12] [13] for static wireless downlinks, where structural properties of the resulting (non-convex) problem are examined. Work in [14] [15] [16] considers game theory approaches to related problems. Work in [17] considers admission pricing to maximize revenue in a data link with multiple traffic classes, and develops an optimal algorithm based on dynamic programming.…”

Section: B Related Workmentioning

confidence: 99%

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Optimal Pricing in a Free Market Wireless Network

Neely

2007

IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications

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We consider an ad-hoc wireless network operating within a free market economic model. Users send data over a choice of paths, and scheduling and routing decisions are updated dynamically based on time varying channel conditions, user mobility, and current network prices charged by intermediate nodes. Each node sets its own price for relaying services, with the goal of earning revenue that exceeds its time average reception and transmission expenses. We first develop a greedy pricing strategy that maximizes social welfare while ensuring all participants make non-negative profit. We then construct a (non-greedy) policy that balances profits more evenly by optimizing a profit fairness metric. Both algorithms operate in a distributed manner and do not require knowledge of traffic rates or channel statistics. This work demonstrates that individuals can benefit from carrying wireless devices even if they are not interested in their own personal communication.

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Section: B Related Workmentioning

confidence: 99%

“…Thus, h n (τ ) is the same as the maximization metric (16) used in the resource allocation algorithm of SGP. Further note that µ n (τ ) = 0 is always an option in the resource allocation optimization (16), and hence this optimization metric is always non-negative. That is, h n (τ ) ≥ 0 for all τ .…”

Section: B Algorithm Performancementioning

confidence: 99%

Optimal Pricing in a Free Market Wireless Network

Neely

2007

IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications

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“…We extend problem P1 with input parameters defined in Table 1 by adding one origin-destination pair (2,6). The number of travelers traversing the roads from the set P (1,6) 7 ) is set to 12000, the number of travelers using the roads from the set P (2,6) = {r 4 , r 5 }, with r 4 = (l 2 , l 5 ), r 5 = (l 4 , l 7 ) is set to 4000.…”

Section: Scenariomentioning

confidence: 99%

“…The number of travelers traversing the roads from the set P (1,6) 7 ) is set to 12000, the number of travelers using the roads from the set P (2,6) = {r 4 , r 5 }, with r 4 = (l 2 , l 5 ), r 5 = (l 4 , l 7 ) is set to 4000. Then travelers The total toll revenue function is F 2 (k) = …”

Section: Scenariomentioning

confidence: 99%

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Bi-level optimal toll design problem solved by the inverse Stackelberg games approach

Staňková¹,

Olsder²,

Bliemer³

2006

WIT Transactions on the Built Environment, Vol 89

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We consider the special type of Stackelberg games known as inverse (or reverse) Stackelberg games and their application to the problem of bi-level optimal toll design in road traffic systems. On a given strongly connected network we assume a noncooperative game with two levels of players: the road authority as a leader and travelers as followers. We consider the road authority with two possible objectives: It either tries to maximize the total toll revenue or to minimize the total travel time of the network by setting tolls on tollable links, while the travelers minimize their travel costs by choosing their travel behavior.In the analysis of traffic systems, link-travel times are modeled as link performance functions, relating travel time to the volume of traffic on the link. These functions are typically smooth, nonlinear, positive, and strictly increasing with link flow. We define link tolls as functions of one or more link flows of the network. Starting from small networks with several origin-destination pairs we analytically find the optimal toll functions for the road authority with the lower level defined by the deterministic user-equilibrium model.The main contributions of this paper are the application of the new field of inverse Stackelberg games in traffic problems and finding the solution to these problems analytically. To define the toll as a function of the link flows seems to be very practical and can help to solve, for example, the congestion problems in densely populated areas.

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Inverse Stackelberg Public Goods Game with Multiple Hierarchies Under Global and Local Information Structures

2013

J Optim Theory Appl

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Incentive-Based Pricing for Network Games with Complete and Incomplete Information

Cited by 31 publications

References 11 publications

Optimal Pricing in a Free Market Wireless Network

Optimal Pricing in a Free Market Wireless Network

Bi-level optimal toll design problem solved by the inverse Stackelberg games approach

Inverse Stackelberg Public Goods Game with Multiple Hierarchies Under Global and Local Information Structures

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