False-Name-Proof Mechanisms for Path Auctions in Social Networks

We study path auction mechanisms for buying path between two given nodes in a social network, where edges are owned by strategic agents. The well known VCG mechanism is the unique solution that guarantees both truthfulness and efficiency. However, in social network environments, the mechanism is vulnerable to false-name manipulations where agents can profit from placing multiple bids under fictitious names. Moreover, the VCG mechanism often leads to high overpayment. In this paper, we present core-selecting path mechanisms that are robust against false-name bids and address the overpayment problem. Specifically, we provide a new formulation for the core, which greatly reduces the number of core constraints. Based on the new formulation, we present a Vickery-nearest pricing rule, which finds the core payment profile that minimizes the L∞distance to the VCG payment profile. We prove that the Vickery-nearest core payments can be computed in polynomial time by solving linear programs. Our experiment results on real network datasets and reported cost dataset show that our Vickery-nearest core-selecting path mechanism can reduce VCG's overpayment by about 20%.