CAMEO

Abstract

Advertisements are the de-facto currency of the Internet with many popular applications (e.g. Angry Birds) and online services (e.g., YouTube) relying on advertisement generated revenue. However, the current economic models and mechanisms for mobile advertising are fundamentally not sustainable and far from ideal. In particular, as we show, applications which use mobile advertising are capable of using significant amounts of a mobile users' critical resources without being controlled or held accountable. This paper seeks to redress this situation by enabling advertisement supported applications to become significantly more ``user-friendly''. To this end, we present the design and implementation of CAMEO, a new framework for mobile advertising that 1) employs intelligent and proactive retrieval of advertisements, using context prediction, to significantly reduce the bandwidth and energy overheads of advertising, and 2) provides a negotiation protocol and framework that empowers applications to subsidize their data traffic costs by ``bartering'' their advertisement rights for access bandwidth from mobile ISPs. Our evaluation, that uses real mobile advertising data collected from around the globe, demonstrates that CAMEO effectively reduces the resource consumption caused by mobile advertising.