Geo-predictive real-time media delivery in mobile environment

Abstract

Multimedia streaming is one of the most popular services today. When the user is in a mobile scenario, the delivery of multimedia streaming services becomes more challenging. Mobile streaming suffers from discontinuous playback that sometimes impairs user experience. Among other factors, this is also due to the high network bandwidth variation that a user can experience along a path. In some cases, the available bandwidth is close to zero when traversing tunnels or areas where the network capacity goes below what is required for a multimedia session to be pause-less. Typically, media adaptation and rate control are used to fight against variable bandwidth. However, these are usually reactive algorithms, where an event is first detected (e.g., a drop in available bandwidth), and then an action is taken, either by the streaming client or by the server. This action may result just in a mitigation of the problem and not in the complete removal. In this paper we introduce the novel concept of Geo-Predictive mobile streaming. This is a collaborative service that makes use of prediction rather than reaction. Network coverage maps are built with the aid of mobile users; with these maps, the available network bandwidth for each location is recorded in a server, and when a user travels from point A to point B, it is possible to predict well in advance what will be the experienced bandwidth along that route. In case of bandwidth drops, these can be known in advance and media adaptation algorithms can be triggered so that a pause-less media playback experience can be guaranteed to the end users anywhere and all the time.