Reconciling bitter rivals: Towards privacy-aware and bandwidth efficient mobile Ads delivery networks

The use of free mobile services and applications (commonly referred as apps) are becoming increasingly popular. Such services and apps are generally monetized by means of third party advertising. The app developers and ad networks which provide the advertisements to be displayed within apps use every means to maximize their revenue, most often at the expense of the end user. These means of maximizing revenue impact the user in three ways: 1) Through the loss of privacy and control over their data; 2) through the increase in monetary cost due to communications overheads introduced by ad traffic; and 3) by the increase of battery usage. The introduction of rich media advertisements will have even greater implications with respect to the aforementioned bandwidth and battery consumption concerns. In this paper, we propose a novel architecture, called MASTAds, that combines the concepts of opportunistic networks, network intermediaries and predictive regularity of human behavior which enable both cost and energy-efficient ads delivery. In addition, MASTAds allows ad networks to obtain only the necessary information to provide targeted advertisements and high Ads revenues, whilst still preserving the user privacy.