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International Workshop on Internet and Network Economics

WINE 2008: Internet and Network Economics pp 286–294Cite as

Taxing Subnetworks

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5385))

Abstract

We study taxes in the well-known game theoretic traffic model due to Wardrop. Given a network and a subset of edges, on which we can impose taxes, the problem is to find taxes inducing an equilibrium flow of minimal network-wide latency cost. If all edges are taxable, then marginal cost pricing is known to induce the socially optimal flow for arbitrary multi-commodity networks. In contrast, if only a strict subset of edges is taxable, we show NP-hardness of finding optimal taxes for general networks with linear latency functions and two commodities. On the positive side, for single-commodity networks with parallel links and linear latency function, we provide a polynomial time algorithm for finding optimal taxes.

Supported by the DFG GK/1298 “AlgoSyn” and by the German Israeli Foundation (GIF) under contract 877/05.

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Author information

Authors and Affiliations

  1. Department of Computer Science, RWTH Aachen University, Germany

    Martin Hoefer, Lars Olbrich & Alexander Skopalik

Authors
  1. Martin Hoefer
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  2. Lars Olbrich
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  3. Alexander Skopalik
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Editor information

Editors and Affiliations

  1. Computer Science Division, University of California at Berkeley, Berkeley, CA, USA

    Christos Papadimitriou

  2. Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

    Shuzhong Zhang

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Hoefer, M., Olbrich, L., Skopalik, A. (2008). Taxing Subnetworks. In: Papadimitriou, C., Zhang, S. (eds) Internet and Network Economics. WINE 2008. Lecture Notes in Computer Science, vol 5385. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92185-1_35

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  • DOI: https://doi.org/10.1007/978-3-540-92185-1_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92184-4

  • Online ISBN: 978-3-540-92185-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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