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.     

Optimized scalable cache management for video streaming system

An important research issue in video streaming is how to efficiently utilize the network resources to provide clients instant access to multiple video objects. Caching strategy and transmission scheme are the two essential points inside the video streaming framework. Recent research efforts on them are not sufficient due to their inflexible support for scalable encoded video streams and heterogeneous requests from clients. In this paper, we propose an optimized caching strategy (OCS) and a scalable transmission scheme (STS) for scalable coded video streaming. By exploring the characteristics of video streaming workload and system design objectives, OCS and STS work efficiently to minimize both network bandwidth cost and user access latency. Firstly, we analyze the caching problem for the proxy-assisted video streaming system and derive a maneuverable caching scenario. Secondly, we develop an efficient transmission scheme for scalable coded videos. Thirdly, we formulate a multi-objective optimization model with closed-form expressions to obtain the optimized caching strategy. Finally, with designed algorithms, an excellent compromise between two competing objectives (minimizing the bandwidth cost and the access latency) is achieved. We start our evaluation by studying the optimized caching strategy for a single video object. Then we apply the strategy to multiple video objects and illustrate the tradeoff between the optimization objectives. Our evaluation results show that compared with other caching strategies, the proposed optimized scalable caching strategy can achieve a significant reduction in bandwidth cost with even a small proxy cache size. Meanwhile, the best performance (in terms of bandwidth cost) is obtained together with the proposed scalable batch-patching transmission scheme.

Seamless switching of scalable video bitstreams for efficient streaming

Efficient adaptation to channel bandwidth is broadly required for effective streaming video over the Internet. To address this requirement, a novel seamless switching scheme among scalable video bitstreams is proposed in this paper. It can significantly improve the performance of video streaming over a broad range of bit rates by fully taking advantage of both the high coding efficiency of nonscalable bitstreams and the flexibility of scalable bitstreams, where small channel bandwidth fluctuations are accommodated by the scalability of a single scalable bitstream, whereas large channel bandwidth fluctuations are tolerated by flexible switching between different scalable bitstreams. Two main techniques for switching between video bitstreams are proposed. Firstly, a novel coding scheme is proposed to enable drift-free switching at any frame from the current scalable bitstream to one operated at lower rates without sending any overhead bits. Secondly, a switching-frame coding scheme is proposed to greatly reduce the number of extra bits needed for switching from the current scalable bitstream to one operated at higher rates. Compared with existing approaches, such as switching between nonscalable bitstreams and streaming with a single scalable bitstream, our experimental results clearly show that the proposed scheme brings higher efficiency and more flexibility in video streaming.     

FJND-based fuzzy rate control of scalable video for streaming applications

Multimedia Tools and Applications - A fuzzy rate controller with buffer constraint in combination with a perceptual quality controller is proposed for streaming applications of the AVC/H.264...     

SVCEval-RA: an evaluation framework for adaptive scalable video streaming

Multimedia content adaption strategies are becoming increasingly important for effective video streaming over the actual heterogeneous networks. Thus, evaluation frameworks for adaptive video play an important role in the designing and deploying process of adaptive multimedia streaming systems. This paper describes a novel simulation framework for rate-adaptive video transmission using the Scalable Video Coding standard (H.264/SVC). Our approach uses feedback information about the available bandwidth to allow the video source to select the most suitable combination of SVC layers for the transmission of a video sequence. The proposed solution has been integrated into the network simulator NS-2 in order to support realistic network simulations. To demonstrate the usefulness of the proposed solution we perform a simulation study where a video sequence was transmitted over a three network scenarios. The experimental results show that the Adaptive SVC scheme implemented in our framework provides an efficient alternative that helps to avoid an increase in the network congestion in resource-constrained networks. Improvements in video quality, in terms of PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity Index) are also obtained.     

基于H.264可伸缩视频流的自适应媒体播放算法

为了应对H.264可伸缩视频编码（SVC）应用中网络特性的波动,提出了一种预测播放中断与缓冲区溢出风险进行及早调节的自适应媒体播放(AMP)算法。该算法估算网络流量与视频图像组（GOP）结构中各帧长度用于风险预测,通过K步调节过程实现良好的调节平滑性与速度,并利用SVC的可伸缩性尽量减少溢出带来的质量损失。仿真结果表明,该算法在抑制播放中断、处理缓冲区溢出与抖动性能等方面,优于现行的平滑AMP与常规AMP算法。     

IEEE 802.11e网络中传输可分级视频流的调度方案

在保证可分级视频流延时要求的情况下,为了有效提高其在无线网络中传输的带宽利用率,提出了一种新的调度方案。该方案利用可分级视频流的分解特性以及不同的流采用不同的调度周期来提高带宽利用率。数值结果表明该方案非常有效,特别是当物理层传输速率较大的时候,其有效性更加明显。     

Complexity of cloud-based transcoding platform for scalable and effective video streaming services

Nowadays, a fast network improves the quality of our daily life and we can enjoy a variety of services over the Internet. Different types of media streaming services have been proposed and utilized as the network speed is now sufficiently fast to deliver high-quality live streaming. Usually, different media streaming services deliver streaming data by using different protocols such as the real-time message protocol (RTMP), real-time streaming protocol (RTSP), and Windows media HTTP streaming protocol (WMSP). In this paper, we propose and implement a cloud-based scalable and cost-effective video streaming transcoding service platform to provide the service of changing real-time streaming protocols (RTMP/RTSP) and codecs (H.263/H.264). A transcoder dispatching problem (TDP) over the cloud platform is also defined, which attempts to serve all the transcoding requests by minimizing the cost of virtual machines. Further, a transcoder dispatching algorithm and an online transcoder dispatching algorithm are proposed for the TDP. These algorithms are implemented on the Amazon EC2 platform. Experimental results demonstrate that by renting different levels of virtual machines dynamically and intelligently, we can provide a scalable and cost-effective transcoding service for bridging heterogeneous streaming media.     

An efficient scheduling algorithm for scalable video streaming over P2P networks

During recent years, the Internet has witnessed rapid advancement in peer-to-peer (P2P) media streaming. In these applications, an important issue has been the block scheduling problem, which deals with how each node requests the media data blocks from its neighbors. In most streaming systems, peers are likely to have heterogeneous upload/download bandwidths, leading to the fact that different peers probably perceive different streaming quality. Layered (or scalable) streaming in P2P networks has recently been proposed to address the heterogeneity of the network environment. In this paper, we propose a novel block scheduling scheme that is aimed to address the P2P layered video streaming. We define a soft priority function for each block to be requested by a node in accordance with the block’s significance for video playback. The priority function is unique in that it strikes good balance between different factors, which makes the priority of a block well represent the relative importance of the block over a wide variation of block size between different layers. The block scheduling problem is then transformed to an optimization problem that maximizes the priority sum of the delivered video blocks. We develop both centralized and distributed scheduling algorithms for the problem. Simulation of two popular scalability types has been conducted to evaluate the performance of the algorithms. The simulation results show that the proposed algorithm is effective in terms of bandwidth utilization and video quality.     

WuKong: a practical video streaming service based on native BitTorrent and scalable video coding

Many researches on peer-to-peer video streaming have focused on dealing with highly dynamic, high-churn P2P environment. Most of P2P streaming protocols were modified from a P2P file sharing protocol. Inspired by the high performance on peer-to-peer file sharing of BitTorrent, we propose an overlaying streaming mechanism on the native BitTorrent protocol and realize a practical P2P video streaming service, called WuKong. WuKong not only takes advantages of BitTorrent but also combines the video scalability of layered video coding. In this paper, we depict an overlaid streaming mechanism in WuKong and an adaptive layer-downloading process to balance between the video quality and bandwidth utilization on heterogeneous peers. WuKong is carried out by using an open-sourced library of the BitTorrent protocol, coding schemes of the Windows Media Video (WMV), and the Scalable Video Coding (SVC). We measured and compared the service quality of end-users served by WuKong on heterogeneous peers. In addition, we evaluated the effectiveness of WuKong with peers that are randomly joining and leaving the P2P network. The results show that WuKong not only provides high quality P2P video streaming services but also supports different scaling abilities over heterogeneous devices.     

A performance evaluation of scalable live video streaming with nano data centers

To improve the efficiency and the quality of a service, a network operator may consider deploying a peer-to-peer architecture among controlled peers, also called here nano data centers, which contrast with the churn and resource heterogeneity of peers in uncontrolled environments. In this paper, we consider a prevalent peer-to-peer application: live video streaming. We demonstrate how nano data centers can take advantage of the self-scaling property of a peer-to-peer architecture, while significantly improving the quality of a live video streaming service, allowing smaller delays and fast channel switching. We introduce the branching architecture for nano datacenters (BAND), where a user can “pull” content from a channel of interest, or content could be “pushed” to it for relaying to other interested users. We prove that there exists an optimal trade-off point between minimizing the number of push, or the number of relaying nodes, and maintaining a robust topology as the number of channels and users get large, which allows scalability. We analyze the performance of content dissemination as users switch between channels, creating migration of nodes in the tree, while flow control insures continuity of data transmission. We prove that this p2p architecture guarantees a throughput independently of the size of the group. Analysis and evaluation of the model demonstrate that pushing content to a small number of relay nodes can have significant performance gains in throughput, start-up time, playback lags and channel switching delays.     

Joint bandwidth allocation,data scheduling and incentives for scalable video streaming over peer-to-peer networks

The overall performance of a peer-to-peer (P2P) scalable streaming system largely depends on the strategies employed in bandwidth allocation, data scheduling and incentives. In this paper, we develop a credit-based content-aware bandwidth auction model for scalable streaming in P2P networks. It formulates multi-overlay multi-layer bandwidth request and allocation problems as auction games. Each peer in the games acts as both auctioneer and player. Being a auctioneer, it maximizes the total revenue (credits) by selling upload bandwidth; Being a player, it uses the credits earned in bandwidth sales to sequentially bid for layer bandwidth so as to maximize the received video quality. Also, a content-aware bidding strategy is proposed, under which the required bandwidth quantity from a peer is determined by the informative video chunks and the marginal net utility that peer could provide, as well as the available credits and the maximum layer bit rate. The convergence of the proposed auction algorithm is mathematically proved. Finally, the performance of the proposed scheme is verified by simulation results.     

Adaptive,incentive and scalable dynamic tree overlay for P2P live video streaming

In this paper, we propose a new multicast tree framework to be used in peer-to-peer (P2P) live video streaming systems. The proposed system, adapts the tree links under high peer churn and runs in a totally distributed manner. In order to provide this dynamism and seamless streaming at the same time, we propose a cross layer design involving scalable video codec, backup parents and hierarchical clusters. The performance of the system is measured in real world environment PlanetLab that has nodes distributed all over the world. The experiments show that the proposed system provides high quality of experience (QoE) in terms of Peak Signal to Noise Ratio (PSNR), playback delay and duration of pauses. The proposed system also provides incentive mechanism to its users.     

Objective quality definition of scalable video coding and its application for optimal streaming of FGS-coded videos

With the proliferation of video contents widely distributed over the Internet and the progress of video coding (e.g., H.264/AVC) and transmission technologies, more challenges need to overcome in order to meet the requirements of all users with diverse terminals. Video streaming over IP and wireless becomes a popular issue since the new century.However, there is little work concerning the quantitative analysis on the objective quality of streaming videos. Thus a strict definition of the objective quality and quality variation of scalable video coding (SVC) is required, in order to efficiently transmit video contents over Internet and wireless and reach an attainable subjective quality perception for end-users. Since FGS (fine granularity scalability) video is coded in bit planes, its enhancing layer can be truncated arbitrarily, as a case study of scalable video coding, an objective quality definition for FGS-coded video is introduced in this paper, based on MSE (mean square error) and PSNR (peak signal-to-noise ratio). This definition can also be generalized to any layered scalable coding videos, such as the traditional layered videos in BL + ELs (base layer + enhancing layers) formats or H.264/AVC in BL + CGS (coarse granularity scalability) + FGS structures, and it can be applied to design optimal algorithms for video streaming. Furthermore, It can also be taken as a measure to assess the subjective quality of streaming videos, by incorporating user preferences and terminal capacities.According to this definition, a quality optimal problem of scene in video segments is formulated and solved using the state transfer graph and dynamic programming. The optimal transmission policy is also obtained and compared with a real-time transmission algorithm. Different aggregation levels (segmentation granularity) of video segments for optimal transmission are also examined by experimental data. Simulation results validate our observations.     

Perceptual hash function for scalable video

Perceptual hash functions are important for video authentication based on digital signature verifying the originality and integrity of videos. They derive hashes from the perceptual contents of the videos and are robust against the common content-preserving operations on the videos. The advancements in the field of scalable video coding call for efficient hash functions that are also robust against the temporal, spatial and bit rate scalability features of the these coding schemes. This paper presents a new algorithm to extract hashes of scalably coded videos using the 3D discrete wavelet transform. A hash of a video is computed at the group-of-frames level from the spatio-temporal low-pass bands of the wavelet-transformed groups-of-frames. For each group-of-frames, the spatio-temporal low-pass band is divided into perceptual blocks and a hash is derived from the cumulative averages of their averages. Experimental results demonstrate the robustness of the hash function against the scalability features and the common content-preserving operations as well as the sensitivity to the various types of content differences. Two critical properties of the hash function, diffusion and confusion, are also examined.     

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.     

A scalable cost-effective video broadcasting system for on-demand video services

Recent years have seen intensive investigations of Periodic Broadcast, an attractive paradigm for broadcasting popular videos. In this paradigm, the server simply broadcasts segments of a popular video periodically on a number of communication channels. A large number of clients can be served simultaneously by tuning into these channels to receive segments of the requested video. A playback can begin as soon as a client can access the first segment. Periodic Broadcast guarantees a small maximum service delay regardless of the number of concurrent clients. Existing periodic broadcast techniques are typically evaluated through analytical assessment. While these results are good performance indicators, they cannot demonstrate subtle implementation difficulty that can prohibit these techniques from practical deployment. In this paper, we present the design and implementation of a video broadcasting system based on our periodic broadcast scheme called Striping Broadcast. Our experience with the system confirms that the system offers a low service delay close to its analytical guaranteed delay while requiring small storage space and low download bandwidth at a client.