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The QUIC transport protocol represents a significant evolution in web transport technologies, offering improved performance and reduced latency compared to traditional protocols like TCP. Given the growing number of QUIC implementations,…
Vision-language models (VLMs) could power real-time assistants and autonomous agents, but they face a critical challenge: understanding near-infinite video streams without escalating latency and memory usage. Processing entire videos with…
Although HTTP-based video streaming can easily penetrate firewalls and profit from Web caches, the underlying TCP may introduce large delays in case of a sudden capacity loss. To avoid an interruption of the video stream in such cases we…
Rate adaptation is one of the most important issues in dynamic adaptive streaming over HTTP (DASH). Due to the frequent fluctuations of the network bandwidth and complex variations of video content, it is difficult to deal with the varying…
The rapid development of multimedia and communication technology has resulted in an urgent need for high-quality video streaming. However, robust video streaming under fluctuating network conditions and heterogeneous client computing…
Motivated by the prowess of deep learning (DL) based techniques in prediction, generalization, and representation learning, we develop a novel framework called DeepQoE to predict video quality of experience (QoE). The end-to-end framework…
Point cloud video has been widely used by augmented reality (AR) and virtual reality (VR) applications as it allows users to have an immersive experience of six degrees of freedom (6DoFs). Yet there is still a lack of research on quality of…
Multimodal large language models (MLLMs) have made significant progress in visual-language reasoning, but their ability to efficiently handle long videos remains limited. Despite recent advances in long-context MLLMs, storing and attending…
MPEG has recently proposed Server and Network Assisted Dynamic Adaptive Streaming over HTTP (SAND-DASH) for video streaming over the Internet. In contrast to the purely client-based video streaming in which each client makes its own…
The rapid rise of large language models (LLMs) in text streaming services has introduced significant cost and Quality of Experience (QoE) challenges in serving millions of daily requests, especially in meeting Time-To-First-Token (TTFT) and…
Extended Reality (XR) is an important service in the 5G network and in future 6G networks. In contrast to traditional video on demand services, real-time XR video is transmitted frame-by-frame, requiring low latency and being highly…
This paper presents a Brownian-approximation framework to optimize the quality of experience (QoE) for real-time video streaming in wireless networks. In real-time video streaming, one major challenge is to tackle the natural tension…
Short video streaming platforms have gained immense popularity in recent years, transforming the way users consume video content. A critical aspect of user interaction with these platforms is the swipe gesture, which allows users to…
The predominant use of wireless access networks is for media streaming applications, which are only gaining popularity as ever more devices become available for this purpose. However, current access networks treat all packets identically,…
Over the recent years, research and development in adaptive bitrate (ABR) algorithms for live video streaming have been successful in improving users' quality of experience (QoE) by reducing latency to near real-time levels while delivering…
This paper presents VideoStreaming, an advanced vision-language large model (VLLM) for video understanding, that capably understands arbitrary-length video with a constant number of video tokens streamingly encoded and adaptively selected.…
The knowledge of future throughput variations in mobile networks becomes more and more possible today thanks to the rich contextual information provided by mobile applications and services and smartphone sensors. It is even likely that such…
Transitioning Multimodal Large Language Models (MLLMs) from offline to online streaming video understanding is essential for continuous perception. However, existing methods lack flexible adaptivity, leading to irreversible detail loss and…
Over the last few years, the evolution of network and user handsets' technologies, have challenged the telecom industry and the Internet ecosystem. Especially, the unprecedented progress of multimedia streaming services like YouTube, Vimeo…
Dynamic Adaptive Streaming over HTTP (DASH) has demonstrated to be an emerging and promising multimedia streaming technique, owing to its capability of dealing with the variability of networks. Rate adaptation mechanism, a challenging and…