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2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06) (2006)
Berkeley, California
Oct. 21, 2006 to Oct. 24, 2006
ISSN: 0272-5428
ISBN: 0-7695-2720-5
pp: 77-86
Elliot Anshelevich , Princeton University, USA
Bruce Shepherd , Bell Labs, USA
Gordon Wilfong , Bell Labs, USA
We introduce a game theoretic model of network formation in an effort to understand the complex system of business relationships between various Internet entities (e.g., Autonomous Systems, enterprise networks, residential customers). This system is at the heart of Internet connectivity. In our model we are given a network topology of nodes and links where the nodes (modeling the various Internet entities) act as the players of the game, and links represent potential contracts. Nodes wish to satisfy their demands, which earn potential revenues, but nodes may have to pay (or be paid by) their neighbors for links incident to them. By incorporating some of the qualities of Internet business relationships, we hope that our model will have predictive value. Specifically, we assume that contracts are either customer-provider or peering contracts. As often occurs in practice, we also include a mechanism that penalizes nodes if they drop traffic emanating from one of their customers. <p>For a natural objective function, we prove that the price of stability is at most 2. With respect to social welfare, however, the prices of anarchy and stability can both be unbounded, leading us to consider how much we must perturb the system to obtain good stable solutions. We thus focus on the quality of Nash equilibria achievable through centralized incentives: solutions created by an "altruistic entity" (e.g., the government) able to increase individual payouts for successfully routing a particular demand. We show that if every payout is increased by a factor of 2, then there is a Nash equilibrium as good as the original centrally defined social optimum. We also show how to find equilibria efficiently in multicast trees. Finally, we give a characterization of Nash equilibria as flows of utility with certain constraints, which helps to visualize the structure of stable solutions and provides us with useful proof techniques.</p>

E. Anshelevich, B. Shepherd and G. Wilfong, "Strategic Network Formation through Peering and Service Agreements," 2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06)(FOCS), Berkeley, California, 2006, pp. 77-86.
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