On random sampling auctions for digital goods

In the context of auctions for digital goods, an interesting Random Sampling Optimal Price auction (RSOP) has been proposed by Goldberg, Hartline and Wright; this leads to a truthful mechanism. Since random sampling is a popular approach for auctions that aims to maximize the seller’s revenue, this method has been analyzed further by Feige, Flaxman, Hartline and Kleinberg, who have shown that it is 15-competitive in the worst case – which is substantially better than the previously proved bounds but still far from the conjectured competitive ratio of 4. In this paper, we prove that RSOP is indeed 4-competitive for a large class of instances in which there are at least 6 people receiving the item at the optimal uniform price. We also show that it is 4.68 competitive for the small class of remaining instances thus leaving a negligible gap between the lower and upper bound. We employ a mix of probabilistic techniques and dynamic programming to compute these bounds.

• Type: Conference
• Year: 2009
• Where: SIGECOM
• Authors: Saeed Alaei, Azarakhsh Malekian, Aravind Srinivasan
• Keywords: Conjectured Competitive Ratio, Information Management, Random Sampling, Sampling Optimal Price, SIGECOM 2009