We investigate streaming over multiple links. A file is split into small units called chunks that may be requested on the various links according to some policy, and received after some random delay. After a start-up time called pre-buffering time, received chunks are played at a fixed speed. There is starvation if the chunk to be played has not yet arrived. We provide lower bounds (fundamental limits) on the starvation probability of any policy. We further propose simple, order-optimal policies that require no feedback. For general delay distributions, we provide tractable upper bounds for the starvation probability of the proposed policies, allowing to select the pre-buffering time appropriately. We specialize our results to: (i) links that employ CSMA or opportunistic scheduling at the packet level, (ii) links shared with a primary user (iii) links that use fair rate sharing at the flow level. We consider a generic model so that our results give insight into the design and performance of media streaming over (a) wired networks with several paths between the source and destination, (b) wireless networks featuring spectrum aggregation and (c) multi-homed wireless networks.
Actor-Critic Scheduling for Path-Aware Air-to-Ground Multipath Multimedia Delivery
Institute of Information Science and Technologies (ISTI), CNR（意大利国家研究委员会信息科学与技术研究所）；CNIT - National Inter-University Consortium for Telecommunications（全国大学间电信联盟）；University of Pisa（比萨大学）
Flow Level QoE of Video Streaming in Wireless Networks
流媒体服务的体验质量（Quality of Experience，QoE）经常由于频繁的播放中断而降低。为了减轻中断，媒体播放器在开始播放之前以延迟为代价预取流媒体内容。我们从流动力学的角度研究流媒体的QoE。首先，当流媒体用户随机加入网络并在下载完成后离开时，为QoE开发了一个框架。我们使用偏微分方程（PDE）计算预取延迟的分布，并使用常微分方程（ODE）的CBR流的播放缓冲区饥饿的概率生成函数。其次，我们扩展了我们的框架，以表征在基站的机会主义调度所造成的吞吐量变化，以及VBR流的回放变化。我们的研究表明，流动力学是播放饥饿的根本原因。流媒体服务的QoE由机会调度的平均吞吐量和平均播放速率等第一时刻决定。而吞吐量和回放速率的变化对饥饿行为的影响非常有限。
Morphe: High-Fidelity Generative Video Streaming with Vision Foundation Model
School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen（科学与工程学院，香港中文大学（深圳））；Shenzhen Future Network of Intelligence Institute（深圳未来网络智能研究院）；Wangxuan Institute of Computer Technology, Peking University（王轩计算机技术研究所，北京大学）
