Time-Dependent Pricing for Mobile Data From Economic Theory to Trial Deployment

Dr. Sangtae Ha
Princeton University


Abstract

In an era of $10/GB overage fees and 108% growth in demand for mobile data, Smart Data Pricing (SDP) will play a major role in ensuring the sustainability and economic viability of the Internet. SDP includes time/location/app/congestion dependent pricing, usage based pricing with demand shaping, intelligent offloading, proactive caching, sponsored content, quota-aware content distribution and any combination of the above. In particular, Time-Dependent Pricing (TDP) addresses the problem by considering when a user consumes data, in addition to how much is used. While TDP for mobile data has been discussed for several decades, no experimental study has been conducted to investigate a functional prototype. To this end, we developed and implemented TUBE, an architecture that takes TDP from economic theory to a system implementation. This talk summarizes the key ideas of dynamic TDP and presents the prototype and results from a field trial of the first TDP system for mobile data. Our results show that TDP benefits both operators and customers, flattening the temporal fluctuation of demand while allowing users to save money by choosing the time and volume of their usage.