Congestion pricing and user adaptation

Ganesh, Ayalvadi; Laevens, Koenraad; Steinberg, Richard

doi:10.1109/infcom.2001.916288

Cited by 45 publications

(41 citation statements)

References 9 publications

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“…Theoretical frameworks of congestion pricing have been discussed thoroughly by several authors [4][5] [6] [7]. Kelly et al [4] and Low et al [7] show how selfish users, seeking to maximize their own net benefit, can be given the right incentives so as to globally optimize the social benefit.…”

Section: Related Workmentioning

confidence: 99%

“…In tâtonnement, the price is updated iteratively until the aggregate user demand meets bandwidth supply. Tâtonnement-based pricing algorithms have been explored in a number of papers [4][5] [6] [7], where the basic idea is to signal a user the marginal cost it imposes on other users (which is also the price in a market-based resource allocation scenario) as an incentive for adaptive applications to adapt their sending rates. Auctioning has been proposed by researchers in the literature [8][9] [10] as another model that allocates scarce bandwidth efficiently, though there is generally no explicit signaling for price before users send their requests.…”

Section: Introductionmentioning

confidence: 99%

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Comparative study of two congestion pricing schemes: auction and tâtonnement

Wang

Schulzrinne

2004

Computer Networks

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We evaluate two mechanisms for setting prices in a QoS-enhanced network with congestion-sensitive pricing and resource allocation based on users' willingness to pay. In the first model, the congestion-sensitive component of the price is calculated by tâtonnement, with the price adjusted gradually to drive down the user demand to the supply level of network resources. In the second model, each user submits multiple bids for different bandwidths, each bid expressing its willingness to pay a certain premium for the corresponding bandwidth during congestion. Simulations show that both approaches provide greater network availability, revenue, and perceived user-benefit than a congestion-independent policy. Both approaches have generally similar performance in terms of perceived user-benefit. The tâtonnement-based model obtains higher network revenue than the auction-based model. The auction-based model achieves higher network utilization at a given level of perceived user-benefit, but has higher implementation complexity and longer set-up delay for new connections. The proposed auction-based model serves more users than comparable auction-based schemes, and has less signaling overhead and greater certainty of service availability.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparative study of two congestion pricing schemes: auction and tâtonnement

Wang

Schulzrinne

2004

Computer Networks

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“…Pricing mechanisms have been suggested earlier for managing resource allocation and congestion control [1,2]. Researchers have also suggested differentiated pricing schemes based on service and quality [3,4].…”

Section: Introductionmentioning

confidence: 99%

The Dynamics of Price, Revenue, and System Utilization

Jagannathan

Almeroth

2001

Management of Multimedia on the Internet

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Abstract. Content delivery is a growing enterprise in the Internet. Critical to the management of content delivery systems is understanding customer behavior, its impact on the consumption of system resources and how together, these affect revenue. We believe that price dictates overall customer behavior and that understanding the relationship between price and customer behavior is the key to effective system management. To this end, we study the impact of price on revenue and system utilization. Our service model is based on customers being able to refuse content based on their capacity to pay and their willingness to pay the price quoted. We quantify the effects of such customer behavior on revenue and system utilization. Since customer behavior and characteristics are highly varying and not known a priori, we develop an adaptive pricing model which tracks user behavior as well as the arrival process to maximize revenue. We validate it using simulation. Our simulation results indicate that the adaptive pricing scheme generates nearly the same revenue as the theoretical expectation under very dynamic workloads.

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“…Also, some of the algorithms assume the knowledge of the user's utility functions, which is generally not practical. Theoretical frameworks of congestion pricing have been discussed thoroughly by several authors [15] [40][41] [42]. Kelly et al [15] and Low et al [40] show how selfish users, seeking to maximize their own net benefit, can be given the right incentives so as to globally optimize the social benefit.…”

Section: Related Workmentioning

confidence: 99%

“…ECN-based marking has been proposed in [41] to convey congestion information back to the end systems, and the resulting system converges to an optimal system state as long as all utility curves are strictly concave. Instead of only marking the packets, the authors in [42] proposed assigning each packet a price to reflect the con- gestion of the network. These schemes assume network services are best-effort, and rely on a pure market mechanism to maximize social benefit.…”

Section: Related Workmentioning

confidence: 99%

Pricing network resources for adaptive applications in a differentiated services network

Wang

Schulzrinne²

Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer An

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Abstract-The Differentiated Services framework (DiffServ) has been proposed to provide multiple Quality of Service (QoS) classes over IP networks. A network supporting multiple classes of service also requires a differentiated pricing structure. In this work, we propose a pricing algorithm in a DiffServ environment based on the cost of providing different levels of quality of service to different classes, and on long-term average user resource demand of a service class. We also integrate the proposed service-dependent pricing scheme with a dynamic pricing and service negotiation environment by considering a dynamic and congestion-sensitive pricing component. Pricing network services dynamically based on the level of service, usage, and congestion allows a more competitive price to be offered, allows the network to be used more efficiently, and provides a natural and equitable incentive for applications to adapt their service requests according to network conditions. We develop a simulation framework to compare the performance of a network supporting congestion-sensitive pricing and adaptive service negotiation to that of a network with a static pricing policy. Adaptive users adapt to price changes by adjusting their sending rate or selecting a different service class. We also develop the demand behavior of adaptive users based on a physically reasonable user utility function. Simulation results show that a congestion-sensitive pricing policy coupled with user rate adaptation is able to control congestion and allows a service class to meet its performance assurances under large or bursty offered loads, even without explicit admission control. Users are able to maintain a stable expenditure, and allowing users to migrate between service classes in response to price increases further stabilizes the individual service prices. When admission control is enforced, congestion-sensitive pricing still provides an advantage in terms of a much lower connection blocking rate at high loads.

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Congestion pricing and user adaptation

Cited by 45 publications

References 9 publications

Comparative study of two congestion pricing schemes: auction and tâtonnement

Comparative study of two congestion pricing schemes: auction and tâtonnement

The Dynamics of Price, Revenue, and System Utilization

Pricing network resources for adaptive applications in a differentiated services network

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