Network Pricing: How to Induce Optimal Flows Under Strategic Link Operators

Jose Correa*, Cristóbal Guzmán, Thanasis Lianeas, Evdokia Nikolova, Marc Schröder

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

Network pricing games provide a framework for modeling real-world settings with two types of strategic agents: owners (operators) of the network and users of the network. Owners of the network post a price for usage of the link they own so as to attract users and maximize profit; users of the network select routes based on price and level of use by other users. We point out that an equilibrium in these games may not exist, may not be unique and may induce an arbitrarily inefficient network performance. Our main result is to observe that a simple regulation on the network owners market solves all three issues above. Specifically, if an authority could set appropriate caps (upper bounds) on the tolls (prices) operators can charge, then: the game among the link operators has a unique and strong Nash equilibrium and the users' game results in a Wardrop equilibrium that achieves the optimal total delay. We call any price vector with these properties a great set of tolls. As a secondary objective, we want to compute great tolls that minimize total users' payments and we provide a linear program that does this. We obtain multiplicative approximation results compared to the optimal total users' payments for arbitrary networks with polynomial latencies of bounded degree, while in the single-commodity case we obtain a bound that only depends on the topology of the network. Lastly, we show how the same mechanism of setting appropriate caps on the allowable prices extends to the model of elastic demands.
Original languageEnglish
Title of host publicationEC '18: Proceedings of the 2018 ACM Conference on Economics and Computation
PublisherAssociation for Computing Machinery (ACM)
Pages375-392
DOIs
Publication statusPublished - Jun 2018
Externally publishedYes

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