Simple, optimal and efficient auctions

Proceedings of the 7th International Workshop, WINE 2011, Singapore, December 11-14, 2011.We study the extent to which simple auctions can simultaneously achieve good revenue and efficiency guarantees in single-item settings. Motivated by the optimality of the second price auction with monopoly reserves when the bidders’ values are drawn i.i.d. from regular distributions [12], and its approximate optimality when they are drawn from independent regular distributions [11], we focus our attention to the second price auction with general (not necessarily monopoly) reserve prices, arguably one of the simplest and most intuitive auction formats. As our main result, we show that for a carefully chosen set of reserve prices this auction guarantees at least 20% of both the optimal welfare and the optimal revenue, when the bidders’ values are distributed according to independent, not necessarily identical, regular distributions. We also prove a similar guarantee, when the values are drawn i.i.d. from a—possibly irregular—distribution.National Science Foundation (U.S.) (award CCF-0953960)National Science Foundation (U.S.) (CCF-1101491

On the Ratio of Revenue to Welfare in Single-Parameter Mechanism Design

What fraction of the potential social surplus in an environment can be extracted by a revenue-maximizing monopolist? We investigate this problem in Bayesian single-parameter environments with independent private values. The precise answer to the question obviously depends on the particulars of the environment: the feasibility constraint and the distributions from which the bidders' private values are sampled. Rather than solving the problem in particular special cases, our work aims to provide universal lower bounds on the revenue-to-welfare ratio that hold under the most general hypotheses that allow for non-trivial such bounds. Our results can be summarized as follows. For general feasibility constraints, the revenue-to-welfare ratio is at least a constant times the inverse-square-root of the number of agents, and this is tight up to constant factors. For downward-closed feasibility constraints, the revenue-to-welfare ratio is bounded below by a constant. Both results require the bidders' distributions to satisfy hypotheses somewhat stronger than regularity; we show that the latter result cannot avoid this requirement.Comment: 15 page

Combinatorial Auction-based Mechanisms for Composite Web Service Selection

Composite service selection presents the opportunity for the rapid development of complex applications using existing web services. It refers to the problem of selecting a set of web services from a large pool of available candidates to logically compose them to achieve value-added composite services. The aim of service selection is to choose the best set of services based on the functional and non-functional (quality related) requirements of a composite service requester. The current service selection approaches mostly assume that web services are offered as single independent entities; there is no possibility for bundling. Moreover, the current research has mainly focused on solving the problem for a single composite service. There is a limited research to date on how the presence of multiple requests for composite services affects the performance of service selection approaches. Addressing these two aspects can significantly enhance the application of composite service selection approaches in the real-world. We develop new approaches for the composite web service selection problem by addressing both the bundling and multiple requests issues. In particular, we propose two mechanisms based on combinatorial auction models, where the provisioning of multiple services are auctioned simultaneously and service providers can bid to offer combinations of web services. We mapped these mechanisms to Integer Linear Programing models and conducted extensive simulations to evaluate them. The results of our experimentation show that bundling can lead to cost reductions compared to when services are offered independently. Moreover, the simultaneous consideration of a set of requests enhances the success rate of the mechanism in allocating services to requests. By considering all composite service requests at the same time, the mechanism achieves more homogenous prices which can be a determining factor for the service requester in choosing the best composite service selection mechanism to deploy