The popularity of the video services on the Internet has evolved various mechanisms that target the Quality of Experience (QoE) optimization of video traffic. The video quality has been enhanced through adapting the sending bitrates. However, rate adaptation alone is not sufficient for maintaining a good video QoE when congestion occurs. This paper presents a cross-layer architecture for video streaming that is QoE-aware. It combines adaptation capabilities of video applications and QoE-aware admission control to optimize the trade-off relationship between QoE and the number of admitted sessions. Simulation results showed the efficiency of the proposed architecture in terms of QoE and number of sessions compared to two other architectures (adaptive architecture and non-adaptive architecture).
Providing a high-quality real-time video streaming experience to mobile users is one of the biggest challenges in cellular networks. This is due to the need of these services for high rates with low variability, which is not easy to accomplish given the competition among (usually a high number of) users for constrained network resources and the high variability of their channel characteristics. A way of improving the user experience is by exploiting their buffers and the ability to provide a constant data rate to everyone, as one of the features of 5G networks. However, the latter is not very …
In this paper, we propose a novel algorithm for video rate adaptation in HTTP Adaptive Streaming (HAS), based on online learning. The proposed algorithm, named Learn2Adapt (L2A), is shown to provide a robust rate adaptation strategy which, unlike most of the state-of-the-art techniques, does not require parameter tuning, channel model assumptions or application-specific adjustments. These properties make it very suitable for mobile users, who typically experience fast variations in channel characteristics. Simulations show that L2A improves on the overall Quality of Experience (QoE) and in par…
Inferring the quality of streaming video applications is important for Internet service providers, but the fact that most video streams are encrypted makes it difficult to do so. We develop models that infer quality metrics (\ie, startup delay and resolution) for encrypted streaming video services. Our paper builds on previous work, but extends it in several ways. First, the model works in deployment settings where the video sessions and segments must be identified from a mix of traffic and the time precision of the collected traffic statistics is more coarse (\eg, due to aggregation). Second,…
The fundamental conflict between the enormous space of adaptive streaming videos and the limited capacity for subjective experiment casts significant challenges to objective Quality-of-Experience (QoE) prediction. Existing objective QoE models exhibit complex functional form, failing to generalize well in diverse streaming environments. In this study, we propose an objective QoE model namely knowledge-driven streaming quality index (KSQI) to integrate prior knowledge on the human visual system and human annotated data in a principled way. By analyzing the subjective characteristics towards str…
The commercialization of Virtual Reality (VR) headsets has made immersive and 360-degree video streaming the subject of intense interest in the industry and research communities. While the basic principles of video streaming are the same, immersive video presents a set of specific challenges that need to be addressed. In this survey, we present the latest developments in the relevant literature on four of the most important ones: (i) omnidirectional video coding and compression, (ii) subjective and objective Quality of Experience (QoE) and the factors that can affect it, (iii) saliency measure…
The combination of video streaming services and wireless networks plays an important role in many fields. In this paper, we present an NS-3-based simulation platform for evaluating and optimizing the performance of the video streaming application over wireless networks. The simulation is designed to provide real-time measurements, and thus it saves the high costs for real equipment. The developed platform consists of the video streaming server, video streaming client, and wireless network environment, where the video streaming operation is implemented under UDP protocol and is equipped with an…
Short video streaming applications have recently gained substantial traction, but the non-linear video presentation they afford swiping users fundamentally changes the problem of maximizing user quality of experience in the face of the vagaries of network throughput and user swipe timing. This paper describes the design and implementation of Dashlet, a system tailored for high quality of experience in short video streaming applications. With the insights we glean from an in-the-wild TikTok performance study and a user study focused on swipe patterns, Dashlet proposes a novel out-of-order video…
360-degree video streaming provides users with immersive experience by letting users determine their field-of-views (FoVs) in real time. To enhance the users' quality of experience (QoE) given their limited bandwidth, recent works have proposed a viewport adaptive 360-degree video streaming model by exploiting the bitrate adaptation in spatial and temporal domains. Under this video streaming model, in this paper, we consider a scenario with a newly generated 360-degree video without viewing history from other users. To maximize the user's QoE, we propose an online bitrate selection algorithm, …
Recent studies into streaming media delivery suggest that performance gains from cache hierarchies such as Information-Centric Networks (ICNs) may be negated by Dynamic Adaptive Streaming (DAS), the de facto method for retrieving multimedia content. The bitrate adaptation mechanisms that drive video streaming clash with caching hierarchies in ways that affect users' Quality of Experience (QoE). Cache performance also diminishes as consumers dynamically select content encoded at different bitrates. In this paper we use the evidence to draw a novel insight: in a cache hierarchy for adaptive stre…
Delivering 360 degree video streaming for virtual and augmented reality presents many technical challenges especially in bandwidth starved wireless environments. Recently, a so-called two-tier approach has been proposed which delivers a basic-tier chunk and select enhancement-tier chunks to improve user experience while reducing network resources consumption. The video chunks are to be transmitted via unicast or multicast over an ultra-dense small cell infrastructure with enough bandwidth where small cells store video chunks in local caches. In this setup, user-cell association algorithms play…
Consumer Virtual Reality (VR) has been widely used in various application areas, such as entertainment and medicine. In spite of the superb immersion experience, to enable high-quality VR on untethered mobile devices remains an extremely challenging task. The high bandwidth demands of VR streaming generally overburden a conventional wireless connection, which affects the user experience and in turn limits the usability of VR in practice. In this paper, we propose FoVR, attention-based hierarchical VR streaming through bandwidth-limited wireless networks. The design of FoVR stems from the insig…
Adaptive bitrate streaming (ABR) has become thede factotechnique for videostreaming over the Internet. Despite a flurry of techniques, achieving high quality ABRstreaming over cellular networks remains a tremendous challenge. First, the design ofan ABR scheme needs to balance conflicting Quality of Experience (QoE) metrics suchas video quality, quality changes, stalls and startup performance, which is even harderunder highly dynamic bandwidth in cellular network. Second, streaming providers havebeen moving towards using Variable Bitrate (VBR) encodings for the video content,which introduces ne…
With the growing of Long Term Evolution (LTE) cellular networks and the increase in the demand of the video services, it is vital to consider the challenges in the streaming services from a different perspective. A perspective that focuses on the streaming services in light of cellular networks challenges, both per layer basis and across multiple layers as well. In this tutorial, we highlight the main challenges that faces the industry of video streaming in the context of cellular networks with a focus on LTE. We also discuss proposed solutions for these challenges while highlighting the limit…
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。
Video services in vehicular networks play a significant role in our daily traveling. In this paper, we propose a cooperative communication scheme to facilitate video data transmission, utilizing the mobility of vehicles and the cooperation among infrastructure and vehicles. To improve the video quality of experience (QoE), i.e., reduce the interruption ratio, quality variation and improve the playback quality, we design a Back Compensation (BC) video transmission strategy with the knowledge of vehicle status information. In addition, we analyze the throughput with one-hop and target-cluster-ba…
With more videos being recorded by edge sensors (cameras) and analyzed by computer-vision deep neural nets (DNNs), a new breed of video streaming systems has emerged, with the goal to compress and stream videos to remote servers in real time while preserving enough information to allow highly accurate inference by the server-side DNNs. An ideal design of the video streaming system should simultaneously meet three key requirements: (1) low latency of encoding and streaming, (2) high accuracy of server-side DNNs, and (3) low compute overheads on the camera. Unfortunately, despite many recent eff…
Vehicle-to-everything (V2X) communication is a key enabler that connects vehicles to neighboring vehicles, infrastructure and pedestrians. In the past few years, multimedia services have seen an enormous growth and it is expected to increase as more devices will utilize infotainment services in the future i.e. vehicular devices. Therefore, it is important to focus on user centric measures i.e. quality-of-experience (QoE) such as video quality (resolution) and fluctuations therein. In this paper, a novel joint video quality selection and resource allocation technique is proposed for increasing …
Inferring the quality of network services is the vital basis of optimization for network operators. However, prevailing real-time video streaming applications adopt encryption for security, leaving it a problem to extract Quality of Service (QoS) indicators of real-time video. In this paper, we propose DaI, a traffic-based real-time video quality estimator. DaI can partially decrypt the encrypted real-time video data and applies machine learning methods to estimate key objective Quality of Experience (QoE) metrics of real-time video. According to the experimental results, DaI can estimate obje…
University of New South Wales（新南威尔士大学）；BITS Pilani（皮拉尼比尔拉理工学院）
Social media, professional sports, and video games are driving rapid growth in live video streaming, on platforms such as Twitch and YouTube Live. Live streaming experience is very susceptible to short-time-scale network congestion since client playback buffers are often no more than a few seconds. Unfortunately, identifying such streams and measuring their QoE for network management is challenging, since content providers largely use the same delivery infrastructure for live and video-on-demand (VoD) streaming, and packet inspection techniques (including SNI/DNS query monitoring) cannot alway…
As the video streaming traffic in mobile networks is increasing, improving the content delivery process becomes crucial, e.g., by utilizing edge computing support. At an edge node, we can deploy adaptive bitrate (ABR) algorithms with a better understanding of network behavior and access to radio and player metrics. In this work, we present ECAS-ML, Edge Assisted Adaptation Scheme for HTTP Adaptive Streaming with Machine Learning. ECAS-ML focuses on managing the tradeoff among bitrate, segment switches, and stalls to achieve a higher quality of experience (QoE). For that purpose, we use machine…
We propose a robust scheme for streaming 360-degree immersive videos to maximize the quality of experience (QoE). Our streaming approach introduces a holistic analytical framework built upon the formal method of stochastic optimization. We propose a robust algorithm which provides a streaming rate such that the video quality degrades below that rate with very low probability even in presence of uncertain head movement, and bandwidth. It assumes the knowledge of the viewing probability of different portions (tiles) of a panoramic scene. Such probabilities can be easily derived from crowdsourced…
In today's Internet, video is the most dominant application and in addition to this, wireless networks such as WiFi, Cellular, and Bluetooth have become ubiquitous. Hence, most of the Internet traffic is video over wireless nodes. There is a plethora of research to improve video streaming to achieve high Quality of Experience (QoE) over the Internet. Many of them focus on wireless nodes. Recent measurement studies often show QoE of video suffers in many wireless clients over the Internet. Recently, many research papers have presented models and schemes to optimize the Adaptive BitRate (ABR) ba…
Adaptive bitrate (ABR) streaming enables video users to adapt the playing bitrate to the real-time network conditions to achieve the desirable quality of experience (QoE). In this work, we propose a novel crowdsourced streaming framework for multi-user ABR video streaming over wireless networks. This framework enables the nearby mobile video users to crowdsource their radio links and resources for cooperative video streaming. We focus on analyzing the social welfare performance bound of the proposed crowdsourced streaming system. Directly solving this bound is challenging due to the asynchrono…
A control-theoretic simplification of adaptive bitrate (ABR) video streaming
Sorbonne Université（索邦大学）；LJLL (CNRS, UMR 7598)（拉格朗日分析、几何及其应用实验室（法国国家科学研究中心，联合研究单位7598））；AL.I.E.N.；Université de Lorraine（洛林大学）；CRAN (CNRS, UMR 7039)（自动控制与纳米技术研究中心（法国国家科学研究中心，联合研究单位7039））
