Adaptive Mobile Traffic Offloading

Cellular operators count on the potential of offloading techniques to relieve their overloaded radio access networks. In this paper, we propose, design, and evaluate a re-injection strategy to finely control the opportunistic distribution of popular contents throughout a hybrid mobile network. The idea is to use the infrastructure resources as seldom as possible. Unlike existing techniques that bind re-injection to statically defined objective functions, our proposal adapts to the current network topology. This turns out to be particularly effective in highly dynamic scenario, where clustering prevent contents to diffuse properly. We assess the performance of our strategy by re-running a realistic large-scale (more than 10,000 nodes) vehicular dataset to disseminate contents under different tolerances to delay. The results show significant savings in the infrastructure load between 55% and 63%.