The weighted majority algorithm
Information and Computation
Fast Approximation Algorithms for Fractional Steiner Forest and Related Problems
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Near-optimal network design with selfish agents
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
The Price of Stability for Network Design with Fair Cost Allocation
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
Adaptive routing with stale information
Proceedings of the twenty-fourth annual ACM symposium on Principles of distributed computing
Fast convergence to Wardrop equilibria by adaptive sampling methods
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
On the topologies formed by selfish peers
Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing
Greedy distributed optimization of multi-commodity flows
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
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A fundamental network design problem is the one of SteinerNetwork Design. The goal is to design a network which is able to support a unit flow for each commodity, at a time, between its source-sink pair. When the flows are unsplittable, this corresponds to the Steiner forest problem and to the problem of sharing cost of the multicast by different users. As a result of greedy selfish behavior of users in the network design game, the overall quality of the resulting solution is often not as good as the globally optimum solution of the underlying problem. We are therefore interested in the problem of designing distributed cost sharing mechanisms that induce the selfish agents to converge to the near-optimum solutions. Our main contribution is showing that 1+ε ratio can be achieved by (non-obvious) unfair cost sharing mechanism, at least for the fractional version of the problem. Our second contribution is showing how to implement our cost sharing mechanism which guarantees fast convergence to a near-optimum equilibrium. We show that for the fractional network design problems, there are indeed such mechanisms that induce greedy agents to converge to (1+ε)-approximate equilibria in linear time.