ICES: Small: Auctions and Optimizations in Ad Exchanges

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Viewers who browse web pages on the Internet are shown display ads such as images and video. Traditionally, web page publishers and advertisers negotiate a priori through sales teams to determine which ads are shown. An emerging way to buy and sell display ads is via automated ad exchanges, which are marketplaces where publishers and advertisers trade ad impressions via real time auctions. This project explores computational, informational and economic aspects of such ad exchange markets. It will abstract suitable models for such markets and study the fundamental challenges, including problems in auction design, online optimization, risk-bounded pricing, real time bidding strategies, and even cryptography. Specific examples include the design of an optimal auction in the presence of a hierarchy of intermediaries who are also auctioneers, determining at each level of this hierarchy which intermediary to call for bids, and proving the integrity of auctions at each level of the hierarchy. Solving these problems requires new methods, concepts and tools from Economics, Finance and Optimization, and Computer Science. Ad exchanges will impact nearly every user on the Internet. Progress on research challenges described here has the potential to directly impact such systems and the experience of nearly every user on the Internet. Further, facing the technical challenges will bring together Computer Scientists and Economists, and also push these disciplines to address very high performance challenges. For example, auction and optimization solutions have to work in tens of milliseconds, the time it takes for users to experience a web page access. This calls for new algorithmic techniques beyond the current start of the art. Finally, a detailed analysis of the role of information in ad exchanges-how much or little information is relevant for the working of the marketplace-is of great interest to Internet users and ultimately the society.