  Ads on the Internet are increasingly sold via ad exchanges such as
RightMedia, AdECN and Doubleclick Ad Exchange. These exchanges allow real-time
bidding, that is, each time the publisher contacts the exchange, the exchange
``calls out'' to solicit bids from ad networks. This aspect of soliciting bids
introduces a novel aspect, in contrast to existing literature. This suggests
developing a joint optimization framework which optimizes over the allocation
and well as solicitation. We model this selective call out as an online
recurrent Bayesian decision framework with bandwidth type constraints. We
obtain natural algorithms with bounded performance guarantees for several
natural optimization criteria. We show that these results hold under different
call out constraint models, and different arrival processes. Interestingly, the
paper shows that under MHR assumptions, the expected revenue of generalized
second price auction with reserve is constant factor of the expected welfare.
Also the analysis herein allow us prove adaptivity gap type results for the
adwords problem.
