Revenue Management of Next Generation Mobile Networks Pantelis Monogioudis November 4, 2010 Abstract We address the increasing gap between the demand for wireless data services and generated revenue. We propose a Revenue Management (RM) solution that in the past solved similar issues in the airline industry. The implementation of such solution requires a rethinking of the problem that nevertheless ends up being something simple: resources are assigned to nested protection buckets that admit or prioritize application flows depending on the economic value of the mobile consumer to the network operator. The implementation of this approach makes extensive use of Machine Learning (ML) algorithms, while the RM is based on an approximate dynamic programming (ADP) optimization solution that allows online revenue-maximizing decisions to be made regarding application flow priorities. RM is envisioned as an essential tool that will allow operators to risk manage the networks against congestion, postpaid/prepaid churn and other revenue affecting indicators. The RM application requires a cloud infrastructure due to its scalability requirements and interfacing with the Wireless Network Guardian (WNG) as well as offline and online charging servers. 1 Introduction Over the last 2 years, the traffic generated by new application phones has raised geometrically while the vast majority of revenues in excess of prescribed postpaid plan tariffs, are reaped by the web platform service providers and their ad-networks. Worse, the revenue from real- time interactive communications such as voice has plummeted due to the commoditization of the voice service and changing demographics with newer generations preferring texting to voice communications 1 . With online video replacing steadily linear television and recently surpassing peer-to-peer as the application that generates the most Internet traffic, the gap between the revenues of distribution networks and ad-networks is poised to increase even further fueled by increased margins from video ads as compared to display ads. Such continuously deteriorating revenue situation ought to call for a significant shift in the business models of operators. Mobile operators respond with cost reductions via merger & acquisitions 1 High definition voice or Facetime-type of services could reverse such trend but many Over The Top (OTT) real time multimedia applications are very expensive for the resources of the network. 1