Pricing in computer networks: Motivation, formulation, and example

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Pricing in computer networks: Motivation, formulation, and example (1993)

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by Ron Cocchi , Scott Shenker , Deborah Estrin , Lixia Zhang

Venue:	IEEE/ACM TRANSACTIONS ON NETWORKING
Citations:	232 - 3 self

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@ARTICLE{Cocchi93pricingin,
    author = {Ron Cocchi and Scott Shenker and Deborah Estrin and Lixia Zhang},
    title = {Pricing in computer networks: Motivation, formulation, and example},
    journal = {IEEE/ACM TRANSACTIONS ON NETWORKING},
    year = {1993}
}

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Abstract

We study the role of pricing policies in multiple service class networks. We first argue that some form of serviceclass sensitive pricing is required for any multiclass service discipline ’ to attain the desired level of performance. Borrowing heavily from the Nash implementation paradigm in economics, we then present an abstract formulation of service disciplines and pricing policies. This formulation allows us to describe more clearly the interplay between service disciplines and pricing policies in determining overall network performance. Effective mrdtichtss service disciplines allow networks to focus resources on performance sensitive applications, while effective pricing policies allow us to spread the benefits of multiple service classes around to all users, rather than just having these benefits remain exclusively with the users of applications that are performance sensitive. Furthermore, service disciplines and pricing policies combine to form the incentive system facing a user; these incentives must be carefully tuned so that user self-interest leads to optimaf overall network performance. Finally, we illustrate some of these concepts through simulation of several simple example networks. In our simulations, we find that it is possible to set the prices so that users of every application type are more satisfied with the combined cost and performance of a network with service-class sensitive prices. For some application types the performance penalty received for requesting a less-than-optimal service class is offset by the reduced price of the service. For the other application types the monetary penalty incurred by using the more expensive, higher-quality service classes is offset by the improved performance they receive.

Keyphrases

computer network service discipline overall network performance performance sensitive application multiclass service discipline service-class sensitive price user self-interest lead desired level higher-quality service class incentive system effective mrdtichtss service discipline abstract formulation multiple service class network less-than-optimal service class effective pricing policy nash implementation paradigm combined cost multiple service class improved performance pricing policy reduced price performance penalty serviceclass sensitive pricing several simple example network monetary penalty application type

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