How Much Can Taxes Help Selfish Routing?

Abstract

We study economic incentives for influencing selfish behavior in networks. We consider a model of selfish routing in which the latency experienced by network traffic on an edge of the network is a function of the edge congestion, and network users are assumed to selfishly route traffic on minimum-latency paths. The quality of a routing of traffic is historically measured by the sum of all travel times, also called the total latency. It is well known that the outcome of selfish routing (a flow at Nash equilibrium) does not minimize the total latency, and that marginal cost pricing -- charging each network user for the congestion effects caused by its presence -- eliminates the inefficiency of selfish routing. However, the principle of marginal cost pricing assumes that taxes cause no disutility to network users; this is appropriate only when collected taxes can be feasibly returned (directly or indirectly) to the users. If this assumption does not hold and we wish to minimize the total user disutility (latency plus taxes paid) -- the total cost -- how should we price the network edges? Intuition may suggest that taxes can never improve the cost of a Nash equilibrium, but the famous Braess's Paradox shows this intuition to be incorrect. We consider strategies for pricing network edges to reduce the cost of a Nash equilibrium. Since levying a sufficiently large tax on an edge effectively removes it from the network, our study generalizes previous work on designing networks for selfish users.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 28, 2005
Accession Number
ADA637874

Entities

People

  • Richard Cole
  • Tim Roughgarden
  • Yevgeniy Dodis

Organizations

  • New York University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Coefficients
  • Commerce
  • Computer Science
  • Computers
  • Congestion
  • Electronic Commerce
  • Flow Network
  • Graphs
  • Guarantees
  • Linear Systems
  • Motivation
  • New York
  • Notation
  • Polynomials
  • Theoretical Computer Science
  • Universities

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Economics
  • Game Theory.