Packet-dispersion techniques and a capacity-estimation methodology
IEEE/ACM Transactions on Networking (TON)
Application Rate Adaptation for Mobile Streaming
WOWMOM '05 Proceedings of the Sixth IEEE International Symposium on World of Wireless Mobile and Multimedia Networks
Service Maps for Heterogeneous Network Environments
MDM '06 Proceedings of the 7th International Conference on Mobile Data Management
An empirical study of bandwidth predictability in mobile computing
Proceedings of the third ACM international workshop on Wireless network testbeds, experimental evaluation and characterization
Mobile video streaming using location-based network prediction and transparent handover
Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video
Towards changing the user perception of mobile communications through geotagged information
Proceedings of the 1st European Workshop on AppRoaches to MObiquiTous Resilience
Video streaming using a location-based bandwidth-lookup service for bitrate planning
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
GTube: geo-predictive video streaming over HTTP in mobile environments
Proceedings of the 5th ACM Multimedia Systems Conference
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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.