Proceedings of the seventeenth ACM symposium on Operating systems principles
User perception of adapting video quality
International Journal of Human-Computer Studies
Dynamic Video Transcoding in Mobile Environments
IEEE MultiMedia
Cross-layer optimization for streaming scalable video over fading wireless networks
IEEE Journal on Selected Areas in Communications
An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP
MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems
An evaluation of dynamic adaptive streaming over HTTP in vehicular environments
Proceedings of the 4th Workshop on Mobile Video
QDASH: a QoE-aware DASH system
Proceedings of the 3rd Multimedia Systems Conference
What happens when HTTP adaptive streaming players compete for bandwidth?
Proceedings of the 22nd international workshop on Network and Operating System Support for Digital Audio and Video
Improving fairness, efficiency, and stability in HTTP-based adaptive video streaming with FESTIVE
Proceedings of the 8th international conference on Emerging networking experiments and technologies
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As the growth of mobile video traffic outpaces that of cellular network speed, industry is adopting HTTP-based adaptive video streaming technology which enables dynamic adaptation of video bit-rates to match changing network conditions. However, recent measurement studies have observed problems in fairness, stability, and efficiency of resource utilization when multiple adaptive video flows compete for bandwidth on a shared wired link. Through experiments and simulations, we confirm that such undesirable behavior manifests itself in cellular networks as well. To overcome these problems, we design an in-network resource management framework, AVIS, that schedules HTTP-based adaptive video flows on cellular networks. AVIS effectively manages the resources of a cellular base station across adaptive video flows. AVIS also provides a framework for mobile operators to achieve a desired balance between optimal resource allocation and user quality of experience. AVIS has three key differentiating features: (1) It optimally computes the bit-rate allocation for each user, (2) It includes a scheduler and per-flow shapers to enforce bit-rate stability of each flow and (3) It leverages the resource virtualization technique to separate resource management of adaptive video flows from regular video flows. We implement a prototype system of AVIS and evaluate it on both a WiMAX network testbed and a LTE system simulator to show its efficacy and scalability.