QoS optimal real-time video streaming in distributed wireless image-sensing platforms

This paper provides a novel real-time video streaming method in distributed wireless image-sensing platforms. It consists of (1) a millimeter-wave (mmW)-based multi-hop routing optimization for real-time video streaming, (2) wireless image-sensing platforms by using the high-efficiency video coding. A mmW wireless communication is a promising technology for increasing capacity in next-generation wireless systems. However, the weakness of mmW signals to (1) do long-distance transmission and (2) survive in non-line-of-sight environments makes the mmW networks need a multi-hop relaying. Thus, this paper focuses on the maximization of video transmission quality of service (QoS) that makes the optimization problem different from the conventional sum-rate maximization. Specifically, this paper develops an algorithm that optimizes the summation of QoS of the individual wireless transmission of different video streams, subject to constraints of separate streams (i.e., minimum requirements in each stream). Experimental results show the proposed approach presents 32 % better performance with 1.84 dB gain in Y-peak signal-to-noise ratio than the widely used max–min flow routing that is generally considered in QoS-sensitive video streaming applications.     

一种基于多描述编码的多路径视频流传输机制

IP网络上数据传输的延迟、丢失和误码,给交互式多媒体通信带来相当大的困难.采用多路径传输技术是有望缓解这一问题的有效途径.本文探讨一种将多描述编码技术与多路径传输技术相结合的视频流传输机制.仿真实验表明,通过多描述编码方法将视频编码为多个流通过多路径传输优于单路径传输.     

一种基于多描述编码的多路径视频流传输机制

IP网络上数据传输的延迟、丢失和误码,给交互式多媒体通信带来相当大的困难。采用多路径传输技术是有望缓解这一问题的有效途径。本文探讨一种将多描述编码技术与多路径传输技术相结合的视频流传输机制。仿真实验表明,通过多描述编码方法将视频编码为多个流通过多路径传输优于单路径传输。     

运动感知基于缓存的自适应视频流传输

目的 基于缓存的自适应视频流传输策略无需估测实时带宽,直接通过缓存变化量与码率的映射函数选取符合当前网络状况的最佳质量码流传输。传统基于缓存的自适应视频传输不考虑内容特征,在码率选择上为不同运动级别视频内容均使用相同的码率映射函数,在不稳定的无线网络环境中高运动强度内容的码率急剧降低会严重伤害用户体验质量（QoE）,提出运动感知基于缓存的自适应视频流传输（MA-BBA）算法。方法 MA-BBA算法根据片段运动级别确定码率映射函数,对运动强度高的内容快速切换到较高码率,而对于运动强度较低的内容则使用较为保守的码率,从而使得缓存资源能够位于安全边界之上且较多分配给高级别运动内容,提高不同运动强度内容的平均质量,使整体QoE得到优化。结果 在公开的无线网络带宽数据集上实现本文MA-BBA算法,基于吞吐量的自适应传输算法（TBA）和基于缓存的自适应传输算法（BBA）。MA-BBA在高运动强度内容的平均质量上比TBA和BBA分别提高1.7%和1.2%,且质量波动区间更小。MA-BBA在平均缓存利用率上达到72%,大大高于TBA的45.9%和BBA的45.4%。结论 MA-BBA算法与现有的码率自适应算法TBA和BBA相比,大大提高了缓存资源利用率,提高了对资源要求最苛刻的高级别运动内容的传输质量,减小码率切换幅度频率,优化了视频服务的整体QoE。     

新颖的实时视频流传输模式

视频传输需要消耗大量的带宽和占用服务器的大量计算资源,为了解决同时传输的视频流数目受到限制的问题,提出了一种新颖的视频流传输框架,多个网络视频服务器组成一个组来共同为多个视频流用户提供服务.在此框架下,研究了一个新的问题——最大化视频流,目标是最大化同时传输的视频流数量.设计了一个启发式的高效算法,与传统的几种视频流传输模式相比,该方法可以支持更多的视频流.     

基于云计算的多路网络流媒体分布式最优存储与分配策略

针对云计算系统在执行任务过程中的能量消耗过多、处理速度不理想等情况,提出一种基于云计算的多路网络流媒体分布式最优存储与分配策略.通过构建基于云计算的数学模型来分析执行任务时的能量消耗情况,采用基于虚拟调度机制的分布式最优存储策略来实现在满足存储需求的情况下减少服务器进行存储时的能量消耗总量,最小化存储成本,并采用基于动态决策规则的分配策略来根据服务器的功率、性能以及负载情况进行任务调度,使云计算系统在满足服务质量要求的条件下,充分利用系统运作能耗,不产生过多空闲能耗.实验及结果分析表明,所提出的分布式最优存储与分配策略在节省能量消耗、提升运行速度上发挥了较好的效果.     

Advanced free viewpoint video streaming techniques

Free-viewpoint video is a new type of interactive multimedia service allowing users to control their viewpoint and generate new views of a dynamic scene from any perspective. The uniquely generated and displayed views are composed from two or more high bitrate camera streams that must be delivered to the users depending on their continuously changing perspective. Due to significant network and computational resource requirements, we proposed scalable viewpoint generation and delivery schemes based on multicast forwarding and distributed approach. Our aim was to find the optimal deployment locations of the distributed viewpoint synthesis processes in the network topology by allowing network nodes to act as proxy servers with caching and viewpoint synthesis functionalities. Moreover, a predictive multicast group management scheme was introduced in order to provide all camera views that may be requested in the near future and prevent the viewpoint synthesizer algorithm from remaining without camera streams. The obtained results showed that even 42 % traffic decrease can be realized using distributed viewpoint synthesis and the probability of viewpoint synthesis starvation can be also significantly reduced in future free viewpoint video services.     

Parallel video streaming optimizing network throughput

In the Internet, video streaming services, in which users can enjoy videos at home, are becoming popular. Video streaming with high definition TV (HDTV) or ultra high definition video (UHDV) quality will be also provided and widely demanded in the future. However, the transmission bit-rate of high-quality video streaming is quite large, so generated traffic flows will cause link congestion. In the Internet, routes that packets take are determined using static link weights, so the network productivity, i.e., the maximum achievable throughout by the network, is determined by the capacity of a bottleneck link with the maximum utilization, although utilizations of many links remain low level. Therefore, when providing streaming services of rich content, i.e., videos with HDTV or UHDV quality, it is important to flatten the link utilization, i.e., reduce the maximum link utilization. We propose that ISPs use multiple servers to deliver rich content to balance the link utilization and propose server allocation and server selection methods for parallel delivery. We evaluate the effect of parallel delivery using 23 actual commercial ISP networks.     

Layer-encoded video in scalable adaptive streaming

Combining the concepts of caching and transmission control protocol (TCP)-friendly streaming of layer-encoded video bears the problem that those videos might not be cached in full quality. Therefore, we focus in this work on the scheduling of retransmissions of missing segments of a cached video in a manner that allows clients to receive the content in an improved quality. In a first step, we conducted subjective assessments of variations in layer-encoded video with the goal to validate existing quality metrics, including our own, which are based on certain assumptions. A statistical analysis of the subjective assessment validates these assumptions. We also show that the frequently used peak signal-to-noise ratio (PSNR) is not an appropriate metric for variations in layer-encoded video. With the insight from the subjective assessment we develop heuristics for retransmission scheduling and prove their applicability by conducting a series of simulations.     

面向视频流媒体的应用层多播技术研究 *

主要关注面向视频流媒体的应用层多播（ALM）技术的研究近况。首先总结了ALM的研究概况和分 类,重点研究了几个针对视频流媒体应用而提出的ALM协议和框架,讨论其中用到的一些前沿技术,分析这些 协议的优缺点,同时给出一些改进思路。最后展望了ALM视频流媒体技术的未来研究方向。     

Enhancing aggregate QoS for video streaming

The IETF's Differentiated Services architecture is designed to provide different types or levels of service for Internet traffic. One of its key features is that traffic flows are aggregated so that routers in the core network only need to distinguish a relatively small number of aggregate flows, even if those flows consist of hundreds or thousands of individual flows. However, network-level QoS differentiation may not satisfy the requirements of many QoS-sensitive applications such as live video streaming, where end-to-end delay and reliability must be guaranteed.

This paper investigates application-level service differentiation for MPEG video streaming in a Diff-Serv-aware MPLS network infrastructure, along with routing support at the network layer. Based on the fact that MPEG video has become one of the most popular formats for Internet (wired and wireless) users, our approach enhances aggregate QoS for video streaming by employing existing application-level knowledge of the MPEG video structure; therefore it requires neither a new video compression algorithm nor additional bandwidth. Several MPEG video dispersion models are proposed and analyzed. Simulation results show that two such strategies are superior to the other tested. In addition, a new routing scheme is proposed to support searching the ‘best’ paths for efficient multi-path video streaming. Through extensive simulations, we demonstrate that our approaches improve the aggregate QoS of MPEG video streams, as well as overall network efficiency.     

User-dependent interactive light field video streaming system

The sheer size and complex structure of light field (LF) videos bring new challenges to their compression and transmission. There have been numerous LF video compression algorithms reported in the literature to date. All of these algorithms compress and transmit all the views of an LF video. However, in some interactive or selective applications where users can choose the area of interest to be displayed, these algorithms generate a significant computational load and enormous data redundancies. In this paper, we propose an interactive LF video streaming system based on a user-dependent view selection scheme and an LF video coding method, which streams only the required data. Specifically, by predicting trajectories and using projection models, the viewing area of users in a limited consecutive number of time slots is firstly calculated, and then a user-dependent view selection method is proposed to determine the selected views of users for streaming. Finally, with the novel LF video sequence formed by only the selected sets of views, an adaptive coding method is presented for different LF video sequences based on users’ gestures. Experimental results illustrate that the proposed interactive LF video streaming system can achieve the best performance compared with other comparison methods.

     

Supporting high-quality video streaming with SDN-based CDNs

Videos and other multimedia contents become increasing popular among users of the Internet nowadays. With the improvement of underlying infrastructure of the Internet, users are allowed to enjoy video contents with much higher quality than last decade. Content delivery networks (CDNs) are a type of content hosting solution that widely used across the Internet. Content providers offload the task of content hosting to CDN providers and redirect users’ requests to CDNs. Video contents, especially high quality videos at real-time has occupying a major part of the Internet traffic. It is challenging to handle such workloads even for a large- scale CDN. Load balancing algorithms are critical to address this issue. However, traditional load balancing algorithms such as round-robin and randomization are unaware of user side requirements. Therefore, it is not uncommon that requests for high-quality videos at real-time are not satisfied. In this paper, we try to fulfill such requests by integrating software-defined networking technology with CDN infrastructure. We also propose revised load balancing algorithms and develop simulations to verify our approaches. The results show that the proposed algorithms achieve much higher user satisfaction in bandwidth-idle environments.     

Adaptive topology formation for peer-to-peer video streaming

In this paper we propose an adaptive P2P video streaming framework to address the challenges due to bandwidth heterogeneity and peer churn on the Internet. This adaptive streaming framework consists of two major components, source rate adaptation and adaptive overlay topology formation, to maximize the video quality and fully utilize the overall peer upload capacity. In the source rate adaptation, the video server adapts the video source rate automatically based on the local measurement of peers’ download rates, so that the P2P network is not overloaded beyond its bandwidth capacity and peers are able to achieve smooth video playback. To combat bandwidth heterogeneity, we propose to construct a desirable link-level homogeneous overlay topology using a Markov chain Monte Carlo method, so that peers achieve an equal per-connection upload/download bandwidth. In this link-level homogeneous network, video flows do not encounter any bottlenecks along the delivery paths, and peers achieve high download rates to ensure smooth video playback. We also design a fully distributed algorithm to implement the dual mechanisms of the adaptive topology formation and the source rate maximization. To evaluate the performance of our streaming framework, we conduct both mathematical analysis and extensive simulations. The simulation results confirm our analysis and show that the proposed distributed algorithm is able to maximize the video playback quality with fast convergence.     

视频流传输中的网络编码综述

网络视频应用增长迅猛,利用网络编码（NC）来提高网络吞吐量和传输可靠性进而改善视频流传输质量成为研究热点。针对如何优化网络编码进行视频流传输这一问题,必须要结合视频流自身特性作出改进并综合考虑所处的网络环境,才能充分发挥网络编码的优势。首先回顾了网络编码的基本概念和方法;然后对网络编码应用于视频流传输时需要考虑的视频业务特性,包括进行不等差错保护以优先保障重要等级视频数据包、降低数据包传输延迟以满足视频流实时性需求、增强网络差错恢复策略以提升传输可靠性等作了分析和归纳;接着阐述了基于网络编码的视频流传输策略在包括P2P、多源协作及内容中心网络等典型场景中的应用;最后对网络编码应用于视频流传输的研究趋势进行展望。     

A survey on peer-to-peer video streaming systems

Video-over-IP applications have recently attracted a large number of users on the Internet. Traditional client-server based video streaming solutions incur expensive bandwidth provision cost on the server. Peer-to-Peer (P2P) networking is a new paradigm to build distributed network applications. Recently, several P2P streaming systems have been deployed to provide live and on-demand video streaming services on the Internet at low server cost. In this paper, we provide a survey on the existing P2P solutions for live and on-demand video streaming. Representative P2P streaming systems, including tree, multi-tree and mesh based systems are introduced. We describe the challenges and solutions of providing live and on-demand video streaming in P2P environment. Open research issues on P2P video streaming are also discussed.

Inter-Object Layer Clustering for scalable video streaming

In this work, we develop an efficient storage technique to support real-time streaming of layer encoded video in a single hard disk. The size of a single hard disk drive will soon be able to hold multi-tera bytes and is going to handle relatively larger number of files. We expect that disk layout in a single disk will be rather critical issue in determining the efficiency of the storage system. We propose a novel storage technique, Inter-Object Layer Clustering for layer encoded video objects. In Inter-Object Layer Clustering, storage is partitioned into two regions: lower layer partition and upper layer partition. Lower and upper layer partition harbor the lower layer and upper layer data blocks across all video objects and cluster them together. We develop an elaborate performance model for this placement scheme. We examine the performance of the proposed technique using analytical formulation as well as a physical experiment. We found that clustering the layers across all objects brings 100% increase in the number of concurrent sessions compared to the case where file is stored in temporal order when the clients’ access bandwidth is narrow. Inter-Object Layer Clustering shows 15% performance improvement compared to the clustering of layers within the objects.     

视频流自适应传输技术研究

对当前视频流技术所采取的各种压缩算法及标准、传输协议、拥塞控制等技术进行了总结与分析,在此基础上对IP网络上的视频流自适应传输技术进行了研究,建立了实现该技术的框架。此技术框架综合了实时的视频自适应编码技术和有效的带宽自适应传输技术。实验结果表明,在对视频流的实时性要求高的应用上具有较突出的优势。     

A DASH-based HEVC multi-view video streaming system

Recent advancement in cameras and image processing technology has generated a paradigm shift from traditional 2D and 3D video to multi-view video (MVV) technology, while at the same time improving video quality and compression through standards such as high efficiency video coding (HEVC). In multi-view, cameras are placed in predetermined positions to capture the video from various views. Delivering such views with high quality over the Internet is a challenging prospect, as MVV traffic is several times larger than traditional video, since it consists of multiple video sequences, each captured from a different angle, requiring more bandwidth than single-view video to transmit MVV. In addition, the Internet is known to be prone to packet loss, delay, and bandwidth variation, which adversely affect MVV transmission. Another challenge is that end users’ devices have different capabilities in terms of computing power, display, and access link capacity, requiring MVV to be adapted to each user’s context. In this paper, we propose an HEVC multi-view system using Dynamic Adaptive Streaming over HTTP to overcome the above-mentioned challenges. Our system uses an adaptive mechanism to adjust the video bit rate to the variations of bandwidth in best effort networks. We also propose a novel scalable way for the multi-view video and depth content for 3D video in terms of the number of transmitted views. Our objective measurements show that our method of transmitting MVV content can maximize the perceptual quality of virtual views after the rendering and hence increase the user’s quality of experience.