EMUNE: Architecture for Mobile Data Transfer Scheduling with Network Availability Predictions

With the mobile communication market increasingly moving towards value-added services, the network cost will need to be included in the service offering itself. This will lead service providers to optimize network usage based on real cost rather than simplified network plans sold to consumers traditionally. Meanwhile, today’s mobile devices are increasingly containing multiple radios, enabling users on the move to take advantage of the heterogeneous wireless network environment. In addition, we observe that many bandwidth intensive services such as video on demand and software updates are essentially non real-time and buffers in mobile devices are effectively unlimited. We therefore propose EMUNE, a new transfer service which leverages these aspects. It supports opportunistic bulk transfers in high bandwidth networks while adapting to device power concerns, application requirements and user preferences of cost and quality. Our proposed architecture consists of an API, a transport service and two main functional units. The well defined API hides all internal complexities from a programmer and provides easy access to the functionalities. The prediction engine infers future network and bandwidth availability. The scheduling engine takes the output of the prediction engine as well as the power and monetary costs, application requirements and user preferences into account and determines which interface to use, when and for how long for all outstanding data transfer requests. The transport service accordingly executes the inferred data transfer schedule. The results from the implementation of EMUNE’s and of the prediction and scheduling engines evaluated against real user data show the effectiveness of the proposed architecture for better utilization of multiple network interfaces in mobile devices.