A cross layer architecture for multicast and unicast video transmission in mobile broadband networks

This paper focuses on the transport of Unicast and Multicast traffic in the mobile broadband networks. The main objective is to allow video streaming applications to adapt its parameters according to 802.16MAC layer conditions and resource availability. For unicast traffic, we propose a cross layer optimizer, named XLO, between scalable video streaming application and IEEE 802.16 MAC layer. XLO uses the existing service flow management messages exchanged between a base station (BS) and a subscriber station (SS) and make them available to the video streaming application via a specific XLO interface. We implemented the XLO in the QualNet simulator and performed extensive simulations using a personalized scalable video traffic generator, capable of streaming video with different data rates and quality levels. We also introduce an enhanced admission control function at the BS that takes into account video adaptability property. The simulation results show the effectiveness of our XLO mechanism for delivering better quality of service. For multicast traffic, we propose a new solution based on superposition coding and make use of scalable video coding in order to optimize the network resources.     

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.     

Partitioning of Multiple Fine-Grained Scalable Video Sequences Concurrently Streamed to Heterogeneous Clients

Fine-grained scalable (FGS) coding of video streams has been proposed in the literature to accommodate client heterogeneity. FGS streams are composed of two layers: a base layer, which provides basic quality, and a single enhancement layer that adds incremental quality refinements proportional to number of bits received. The base layer uses nonscalable coding which is more efficient in terms of compression ratio than scalable coding used in the enhancement layer. Thus for coding efficiency larger base layers are desired. Larger base layers, however, disqualify more clients from getting the stream. In this paper, we experimentally analyze this coding efficiency gap using diverse video sequences. For FGS sequences, we show that this gap is a non-increasing function of the base layer rate. We then formulate an optimization problem to determine the base layer rate of a single sequence to maximize the average quality for a given client bandwidth distribution. We design an optimal and efficient algorithm (called FGSOPT) to solve this problem. We extend our formulation to the multiple-sequence case, in which a bandwidth-limited server concurrently streams multiple FGS sequences to diverse sets of clients. We prove that this problem is NP-Complete. We design a branch-and-bound algorithm (called MFGSOPT) to compute the optimal solution. MFGSOPT runs fast for many typical cases because it intelligently cuts the search space. In the worst case, however, it has exponential time complexity. We also propose a heuristic algorithm (called MFGS) to solve the multiple-sequence problem. We experimentally show that MFGS produces near-optimal results and it scales to large problems: it terminates in less than 0.5 s for problems with more than 30 sequences. Therefore, MFGS can be used in dynamic systems, where the server periodically adjusts the structure of FGS streams to suit current client distributions.     

基于MPEG-4的FGS视频压缩技术的研究

精细可伸缩性视频编码FGS(Fine Granular Scalable)是MPEG-4标准的视频化框架中的关键性的编码技术。FGS编码方法生成两个视频流：基本层码流和增强层码流。基本层码流是必须传输的,并且码率低;增强层码流则根据带宽的实际情况来决定传多少,甚至不传,这种分级性的编码方式和传输方式使视频流有较好的鲁棒性。     

基于 SDN 的密集小蜂窝网络中可伸缩视频传输优化

为了优化多媒体数据在无线网络中的传输,该文将密集型小蜂窝网络、软件定义网络以及可 伸缩视频编码技术相结合,设计了一个完整的多媒体视频传输系统。其中,通过密集型小蜂窝网络基站间的协作,提高无线频谱利用率;通过自适应码率调节技术,为不同用户提供差分服务。该文以最大化用户体验质量为目标,联合决策用户视频质量和无线资源分配。采用李雅普诺夫优化理论,将原问题转化为两个独立的子问题分别进行求解,并给出了仅依赖当前观测信息的低复杂度算法。实验结果显示,该文所提出的算法在动态环境下能够做出较好响应,并且可以实现更高的用户体验。     

The MPEG-4 fine-grained scalable video coding method for multimediastreaming over IP

Real-time streaming of audiovisual content over the Internet is emerging as an important technology area in multimedia communications. Due to the wide variation of available bandwidth over Internet sessions, there is a need for scalable video coding methods and (corresponding) flexible streaming approaches that are capable of adapting to changing network conditions in real time. In this paper, we describe a new scalable video-coding framework that has been adopted recently by the MPEG-4 video standard. This new MPEG-4 video approach, which is known as Fine-Granular-Scalability (FGS), consists of a rich set of video coding tools that support quality (i.e., SNR), temporal, and hybrid temporal-SNR scalabilities. Moreover, one of the desired features of the MPEG-J FGS method is its simplicity and flexibility in supporting unicast and multicast streaming applications over IF     

基于视频业务质量优化的认知无线电传输信道选择

认知无线电网络中,次级用户选择信道的传统技术基于信道特性对传输信道进行随机选择,忽略了应用层视频业务对信道质量的要求。针对该问题提出了一种基于视频业务质量优化的信道选择技术,优化视频业务端到端的传输质量。通过最小化端到端视频失真,跨层优化综合选择物理层传输信道、自适应调制与编码模式以及应用层的编码量化参数。该方法在多信道认知无线电网络下进行了大量的视频传输仿真模拟实验。实验结果表明该方法能够比不含信道选择的跨层优化方法提高认知无线电网络下次级用户的视频传输业务客观质量1.5 dB以上。     

一种基于单环结构的扩展基本层FGS视频编码方法

可分级编码是解决Internet流视频应用中网络带宽不断波动的一种有效方法，所以MPEG-4标准中采用了FGS(fine granularity scalability)编码方法来获得精细颗粒可分级能力，但其代价是编码效率的下降。为解决此问题，现提出在增强层中采用运动补偿的MC加FGS(motion compensation加FGS)结构，用于去除FGS方案中增强层在时域上的冗余，以提高FGS方案编码效率的双环和单环两种方法。在比较了两种结构各自的优缺点后，选定了一种复杂度小、实现简单、效率高的单环结构，并提出了对单环结构的缺陷进行改善的方法。实验结果表明，该方法的编码性能优于MPEG-4 FGS方法。     

Optimal Coding of Multilayer and Multiversion Video Streams

Traditional video servers partially cope with heterogeneous client populations by maintaining a few versions of the same stream with different bit rates. More recent video servers leverage multilayer scalable coding techniques to customize the quality for individual clients. In both cases, heuristic, error-prone, techniques are currently used by administrators to determine either the rate of each stream version, or the granularity and rate of each layer in a multilayer scalable stream. In this paper, we propose an algorithm to determine the optimal rate and encoding granularity of each layer in a scalable video stream that maximizes a system-defined utility function for a given client distribution. The proposed algorithm can be used to compute the optimal rates of multiversion streams as well. Our algorithm is general in the sense that it can employ arbitrary utility functions for clients. We implement our algorithm and verify its optimality, and we show how various structuring of scalable video streams affect the client utilities. To demonstrate the generality of our algorithm, we consider three utility functions in our experiments. These utility functions model various aspects of streaming systems, including the effective rate received by clients, the mismatch between client bandwidth and received stream rate, and the client-perceived quality in terms of PSNR. We compare our algorithm against a heuristic algorithm that has been used before in the literature, and we show that our algorithm outperforms it in all cases.     

Efficient algorithms of video replication and placement on a cluster of streaming servers

A cost-effective approach to building up scalable video streaming servers is to couple a number of streaming servers together in a cluster so as to alleviate the inherent storage and networking constraints of streaming services. In this article, we investigate a crucial problem of video replication and placement on a distributed storage cluster of streaming servers for high quality and high availability services. We formulate it as a combinatorial optimization problem with objectives of maximizing the encoding bit rate and the number of replicas of each video and balancing the workload of the servers. The objectives are subject to the constraints of the storage capacity and the outgoing network-I/O bandwidth of the servers. Under the assumption of single fixed encoding bit rate for all video objects with different popularity values, we give an optimal replication algorithm and a bounded placement algorithm, respectively. We further present an efficient replication algorithm that utilizes the Zipf-like video popularity distributions to approximate the optimal solutions, which can reduce the complexity of the optimal replication algorithm. For video objects with scalable encoding bit rates, we propose a heuristic algorithm based on simulated annealing. We conduct a comprehensive performance evaluation of the algorithms and demonstrate their effectiveness via simulations over a synthetic workload set.     

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.     

异构环境下层次编码多视频源多共享信道分层组播

视频组播是许多当前和将来网络服务的重要组成部分,如视频会议,远程学习、远地展示及视频点播,随着网络传送基础设施的改善和端系统处理能力的增强,组播视频应用日益变得可行,组播视频传输中存在的主要问题是网络送资源的异构性和动态性,其使得视频流的多个接收方都达到可接受的流量特性变得异常困难,目前该问题的一个有效解决方式就是利用自适应的分层视频传输机制,在该机制中,各源产生层次媒体流,并在多个网络信道中传输。对视频会议类的多点到多点视频组播应用,信道往往被所有潜在的发送方共享,任何发送方都可在任何一个共享信道中发送其视频层次。在该多点到多点、共享信道、分层视频组播模型下,一个关键问题就是如何动态确定各视频源层次到各共享组播信道的映射,映射策略直接影响到会话整体视频接收质量和网络带宽利用率。典型的方式是顺序映射,该映射方式同等对待各发送方,但利用该方式,随源数目的增加,在各共享网络信度上会出现带宽可伸缩性问题,而且顺序映射方式无法适应网络传送资源和会话状态的动态变化。为此,该文设计了一种基于接收方反馈信息的自适应的层次映射算法,接收方周期性地将其当前感兴趣的发送方及接收速率的信息反馈给某控制节点,而控制节点就利用当前反馈信息动态地调整映射策略。经证实,该算法始终能比顺序层次映射算法获得更高的整体视频接收质量,并具有高的带宽利用率和很小的复杂度。     

An incentive scheduling mechanism for peer-to-peer video streaming

P2P video streaming networks are found as a scalable solution and an alternative for traditional client–server based video streaming over the Internet. One of the significant issues affecting the success of any P2P streaming network is cooperation between peers. Practical observations have proved the prevalence of free riders in P2P networks that degrade their performance. To solve this problem, using incentive mechanisms, which encourage peers to contribute more in the network, is necessary. In this paper, we designed and proposed a distributed and scalable incentive mechanism for mesh based P2P video streaming networks. In the proposed approach the contribution of the peers is measured and maintained in a distributed fashion. Furthermore, we proposed an incentive sending side scheduler in which peers are served based on their contribution in the network. Our simulation evaluations show the efficiency of the proposed approach in improving the overall perceived video quality by the non-free rider nodes and consequently in the whole network.     

Rate-Distortion Analysis and Quality Control in Scalable Internet Streaming

Rate-distortion (R-D) modeling of video coders has always been an important issue in video streaming; however, few of the traditional R-D models and their performance have been closely examined in the context of scalable (FGS-like) video. To overcome this shortcoming, the first half of the paper models rate-distortion of DCT-based fine-granular scalable coders and derives a simple operational R-D model for Internet streaming applications. Experimental results demonstrate that this R-D result, an extension of the classical R-D formula, is very accurate within the domain of scalable coding methods exemplified by MPEG-4 FGS and H.264 progressive FGS. In the second half of the paper, we examine congestion control and dynamic rate-scaling algorithms that achieve smooth visual quality during streaming using the proposed R-D model. In constant bitrate (CBR) channels, our R-D based quality-control algorithm dramatically reduces PSNR variation between adjacent frames (to less than 0.1 dB in sample sequences). Since the Internet is a changing environment shared by many sources, even R-D based quality control often cannot guarantee nonfluctuating PSNR in variable-bitrate (VBR) channels without the help from an appropriate congestion controller. Thus, we apply recent utility-based congestion control methods to our problem and show how a combination of this approach and our R-D model can benefit future streaming applications     

LION: Layered Overlay Multicast With Network Coding

Recent advances in information theory show that the throughput of a multicast session can be improved using network coding. In overlay networks, the available bandwidth between sender and different receivers are different. In this paper, we propose a solution to improve the throughput of an overlay multicast session with heterogeneous receivers by organizing the receivers into layered data distribution meshes and sending substreams to each mesh using layered coding. Our solutions utilize alternative paths and network coding in each mesh. We first formulate the problem into a mathematical programming, whose optimal solution requires global information. We therefore present a distributed heuristic algorithm. The heuristic progressively organizes the receivers into layered meshes. Each receiver can subscribe to a proper number of meshes to maximize its throughput by fully utilizing its available bandwidth. The benefits of organizing the topology into layered mesh and using network coding are demonstrated through extensive simulations. Numerical results indicate that the average throughput of a multicast session is significantly improved (up to 50% to 60%) with only slightly higher delay and network resource consumption.     

空间可扩展视频编码中增强层上的帧内预测算法研究

针对空间可扩展视频编码,提出了一种新的增强层上的帧内预测算法。该算法充分考虑了相邻层间所固有的空域相关性,在无法正确获取本层邻块预测值的情况下,利用基本层上插值放大后的解码,通过重构宏块来对增强层上的编码宏块进行帧内预测。此外,还在预测过程中,通过引入与图像纹理特征相关联的自适应加权因子对(Wv,Wh)来进一步提高新算法的编码性能。实验结果表明,与H.264标准中的帧内预测算法相比,新算法在保持原有码率和不增加额外的计算复杂度的前提下,可一定程度地提高亮度分量的PSNR值,因此可以作为空间可扩展视频编码中增强层上的帧内编码方案。     

Optimal Channel Adaptation of Scalable Video Over a Multicarrier-Based Multicell Environment

To achieve seamless multimedia streaming services over wireless networks, it is important to overcome inter-cell interference (ICI), particularly in cell border regions. In this regard scalable video coding (SVC) has been actively studied due to its advantage of channel adaptation. We explore an optimal solution for maximizing the expected visual entropy over an orthogonal frequency division multiplexing (OFDM)-based broadband network from the perspective of cross-layer optimization. An optimization problem is parameterized by a set of source and channel parameters that are acquired along the user location over a multicell environment. A suboptimal solution is suggested using a greedy algorithm that allocates the radio resources to the scalable bitstreams as a function of their visual importance. The simulation results show that the greedy algorithm effectively resists ICI in the cell border region, while conventional nonscalable coding suffers severely because of ICI.     

A Multilayered Audiovisual Streaming System Using the Network Bandwidth Adaptation and the Two-Phase Synchronization

Synchronous audiovisual streaming and playout are two of the major issues in the multimedia communication network. However, the past corresponding researches of media synchronization mainly focused on the mono-quality and single-layer (nonscalable) audiovisual data. To overcome challenges of ubiquitous multimedia streaming, a scalable audiovisual coder that can provide flexible scalabilities and adaptive streaming control to adapt to complicated network situations are both required. This paper proposes a multilayered audiovisual streaming scheme to deliver layered audiovisual data synchronously, which is called ML-AVSS. Fine-granular scalability (FGS) and bit-sliced arithmetic coding (BSAC) techniques are used to segment video and audio data into one base-layer and multiple enhancement-layer bitstreams. With advantages of audiovisual layer coding, a de-jitter procedure, a conditional retransmission mechanism and a playout synchronization mechanism are designed to transmit hybrid multilayered audiovisual bitstreams in consideration of the result of a network bandwidth adaptation and the distinct decoding time-complexity. Experimental results show that the proposed ML-AVSS is a feasible streaming scheme to overcome challenges of ubiquitous multimedia streaming, e.g., constrained channel bandwidth, quality degradation, unsmooth playout, etc.     

一种分层P2 P流媒体系统重叠网的构建策略

基于Peer-to-Peer(P2P)技术的流媒体应用具有部署效率高及可扩展性好等突出优势。而采用分层视频编码技术的P2P流媒体系统把原视频流分解为多个视频层数据进行分发,让节点能够选择与自己带宽资源相匹配的视频质量,使其很好地适应节点的异构性。但是各分层视频数据传输的路径存在较大差异,使重叠网构建策略面临更大的挑战。因此定义了基于分层视频编码技术环境下的P2P流媒体重叠网络构建问题,并证明该问题是一个NP难问题。提出了一种构建重叠网的集中启发式算法,同时还提出了一种基于视频组(Streaming Group)的分布式重叠网络构建策略。通过大规模网络仿真实验验证了基于该分布式重叠网构建策略的分层流媒体系统具备低服务器带宽占用、高数据获取率等优点。     

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.