Location-Aided Planning in Mobile Network—Trial Results
Wireless Personal Communications: An International Journal
PRISM: Improving the Performance of Inverse-Multiplexed TCP in Wireless Networks
IEEE Transactions on Mobile Computing
Fine-grained scalable streaming from coarse-grained videos
Proceedings of the 18th international workshop on Network and operating systems support for digital audio and video
DAVVI: a prototype for the next generation multimedia entertainment platform
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Subjective impression of variations in layer encoded videos
IWQoS'03 Proceedings of the 11th international conference on Quality of service
Augmenting mobile 3G using WiFi
Proceedings of the 8th international conference on Mobile systems, applications, and services
Geo-predictive real-time media delivery in mobile environment
Proceedings of the 3rd workshop on Mobile video delivery
MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems
Video streaming using a location-based bandwidth-lookup service for bitrate planning
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Enhancing mobile data offloading with mobility prediction and prefetching
Proceedings of the seventh ACM international workshop on Mobility in the evolving internet architecture
Commute path bandwidth traces from 3G networks: analysis and applications
Proceedings of the 4th ACM Multimedia Systems Conference
Enhancing mobile data offloading with mobility prediction and prefetching
ACM SIGMOBILE Mobile Computing and Communications Review
MASERATI: mobile adaptive streaming based on environmental and contextual information
Proceedings of the 8th ACM international workshop on Wireless network testbeds, experimental evaluation & characterization
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A well known challenge with mobile video streaming is fluctuating bandwidth. As the client devices move in and out of network coverage areas, the users may experience varying signal strengths, competition for the available resources and periods of network outage. These conditions have a significant effect on video quality. In this paper, we present a video streaming solution for roaming clients that is able to compensate for the effects of oscillating bandwidth through bandwidth prediction and video quality scheduling. We combine our existing adaptive segmented HTTP streaming system with 1) an application layer framework for creating transparent multi-link applications, and 2) a location based QoS information system containing GPS coordinates and accompanying bandwidth measurements, populated through crowd-sourcing. Additionally, we use real-time traffic information to improve the prediction by, for example, estimating the length of a commute route. To evaluate our prototype, we performed real-world experiments using a popular tram route in Oslo, Norway. The client connected to multiple networks, and the results show that our solution increases the perceived video quality significantly. Also, we used simulations to evaluate the potential of aggregating bandwidth along the route.