Revenue optimization and fairness control of priced guaranteed and best effort services on an ATM transmission link

Fodor, Gábor; Nordström, Ernst; Blaabjerg, Søren

doi:10.1109/icc.1998.683120

Cited by 7 publications

(6 citation statements)

References 10 publications

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“…Discussions of the role of pricing in the con nection establishment process can also be found in [11][12][13][14]. In networks where a traffic contract or service-level agreement (SLA) is established in advance, it is also possible to charge users according to the accuracy of their traffic descriptor, rewarding customers who provide better information on the statistical behavior of their offered traffic.…”

Section: Pricing and Traffic Managementmentioning

confidence: 99%

“…The network may be viewed as a public good, in which case a benevolent service provider would set prices that maximize some measure of social wel fare [12,27] such as aggregate utility or surplus. Alternatively, the network may be viewed as a private good; in this case, one would expect the service provider to be revenue maximizing, as in [11,18,21,28,29].…”

Section: Utility and Optimization Objectivesmentioning

confidence: 99%

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Pricing for QoS-enabled networks: A survey

DaSilva

2000

IEEE Commun. Surv. Tutorials

200

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A complete solution to the problem of providing adequate quality of service (OoS) to heterogeneous users must take into account the issue of pricing. By adopting an appropriate pricing policy and by setting prices carefully, a service provider will be able to offer the necessary incentives for each user to choose the service that best matches his/her needs, thereby discouraging over-allocation of resources and maximizing revenue and/or social welfare. In this article, we survey some of the recent research in the literature dealing with service pricing in multi-service networks. All of the work surveyed here addresses the relationship between prices and traffic management functions such as congestion control, resource provisioning, and call admission control. We summarize proposed pricing policies for the Internet and for ATM net works, as well as some studies of pricing for general OoS-enabled networks.

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Section: Pricing and Traffic Managementmentioning

confidence: 99%

Section: Utility and Optimization Objectivesmentioning

confidence: 99%

Pricing for QoS-enabled networks: A survey

DaSilva

2000

IEEE Commun. Surv. Tutorials

200

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“…The impact of pricing on the optimal bandwidth sharing strategies, again assuming two traffic classes is considered by Altman et al [19] and by Fodor et al [22].…”

Section: Related Workmentioning

confidence: 99%

On providing blocking probability and throughput guarantees in a multi‐service environment

Fodor¹,

Rácz²,

Telek³

2002

Int J Communication

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SUMMARYAs the Internet evolves from a packet network supporting a single best effort service class towards an integrated infrastructure supporting several service classes}some with QoS guarantees}there is a growing interest in the introduction of admission control and in devising bandwidth sharing strategies, which meet the diverse needs of QoS-assured and elastic services. In this paper we show that the extension of the classical multi-rate loss model is possible in a way that makes it useful in the performance analysis of a future admission control based Internet that supports traffic with peak rate guarantee as well as elastic traffic. After introducing the model, it is applied for the analysis of a single link, where it sheds light on the trade-off between blocking probability and throughput. For the investigation of this trade-off, we introduce the throughput-threshold constraint, which bounds the probability that the throughput of a traffic flow drops below a predefined threshold. Finally, we use the model to determine the optimal parameter set of the popular partial overlap link allocation policy: we propose a computationally efficient algorithm that provides blocking probability-and throughput guarantees. We conclude that the model and the numerical results provide important insights in traffic engineering in the Internet.

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“…Let C denote the link capacity. The system under investigation (with the above assumptions regarding the arrival processes and holding times) is a Continuous Time Markov Chain (CTMC) whose state is uniquely characterized by (n 1 (t), n 2 (t)) where n 1 (t) is the number of stream calls and n 2 (t) is the number of elastic calls on the link at time t (0 [1], [2]. Aby bolo možné pre pružné volania určiť optimálny algoritmus CAC, overili sme na základe modelu spoja zavedeného v [2] pomocou Markovovej teórie rozhodovania rôzne stratégie tarifikovania.…”

Section: System Descriptionmentioning

confidence: 99%

“…Ukážeme, že optimalizácia CAC maximalizuje nielen príjmy, ale tiež zvyšuje pravdepodobnosť blokovania prevádzky tokov s vysokou prioritou a QoS pružného prevádzkového zaťaženia, ak je tarifikačná funkcia použiteľná. [1], [2]. Based on a model of a single link introduced in [2], we evaluate different pricing strategies assigned to elastic calls by determining an optimal CAC using Markov Decision theory.…”

Section: System Descriptionunclassified

Evaluation of Pricing Strategies of Elastic Traffic on a Single Communication Link

Fodor¹,

Marquetant²

2001

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Revenue optimization and fairness control of priced guaranteed and best effort services on an ATM transmission link

Cited by 7 publications

References 10 publications

Pricing for QoS-enabled networks: A survey

Pricing for QoS-enabled networks: A survey

On providing blocking probability and throughput guarantees in a multi‐service environment

Evaluation of Pricing Strategies of Elastic Traffic on a Single Communication Link

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