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Rome, Italy

Oct. 17, 2004 to Oct. 19, 2004

ISBN: 0-7695-2228-9

pp: 295-304

Elliot Anshelevich , Cornell University

Anirban Dasgupta , Cornell University

Jon Kleinberg , Cornell University

Éva Tardos , Cornell University

Tom Wexler , Cornell University

Tim Roughgarden , University of California at Berkeley

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/FOCS.2004.68

ABSTRACT

<p>Network design is a fundamental problem for which it is important to understand the effects of strategic behavior. Given a collection of selfinterested agents who want to form a network connecting certain endpoints, the set of stable solutions — the Nash equilibria — may look quite different from the centrally enforced optimum. We study the quality of the best Nash equilibrium, and refer to the ratio of its cost to the optimum network cost as the price of stability. The best Nash equilibrium solution has a natural meaning of stability in this context — it is the optimal solution that can be proposed from which no user will "defect".</p> <p>We consider the price of stability for network design with respect to one of the most widely-studied protocols for network cost allocation, in which the cost of each edge is divided equally between users whose connections make use of it; this fair-division scheme can be derived from the Shapley value, and has a number of basic economic motivations. We show that the price of stability for network design with respect to this fair cost allocation is O(log k), where k is the number of users, and that a good Nash equilibrium can be achieved via best-response dynamics in which users iteratively defect from a starting solution. This establishes that the fair cost allocation protocol is in fact a useful mechanism for inducing strategic behavior to form near-optimal equilibria. We discuss connections to the class of potential games defined by Monderer and Shapley, and extend our results to cases in which users are seeking to balance network design costs with latencies in the constructed network, with stronger results when the network has only delays and no construction costs. We also present bounds on the convergence time of best-response dynamics, and discuss extensions to a weighted game.</p>

INDEX TERMS

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CITATION

Elliot Anshelevich,
Anirban Dasgupta,
Jon Kleinberg,
Éva Tardos,
Tom Wexler,
Tim Roughgarden,
"The Price of Stability for Network Design with Fair Cost Allocation",

*FOCS*, 2004, 2013 IEEE 54th Annual Symposium on Foundations of Computer Science, 2013 IEEE 54th Annual Symposium on Foundations of Computer Science 2004, pp. 295-304, doi:10.1109/FOCS.2004.68