Scalable Video Coding Streaming Research Articles

Cache-Aware Network Coding-Based Scheduling for SVC Multicast in Wireless Networks with Hard Deadline Constraints

To provide multi-resolution video for heterogeneous users in wireless networks, Scalable Video Coding (SVC) encodes a video bit stream into one base layer and several enhancement layers, on the basis of their contribution in recovering the video correspondingly. However, a decoding dependency is introduced into these layers and artful operation is required for SVC streaming. Meanwhile, each SVC packet is associated with a hard time constraint so that users can recover their desired video quality timely. This paper focuses on the network coding assisted SVC multicast with hard deadline constraints. Specifically, we consider the cache-aware model where users are able to store all received packets and decode out the desired packets when sufficient packets are obtained. We analyze the effect of cached network coded packets on the SVC packets scheduling process and the video quality improvement, and value that effect through assigning proper weight for each packet. We also take multiple factors that affect quality of experience into consideration, such as channel condition, request’s deadline and user’s packets receiving status. Moreover, we adopt the instantly decodable network coding (IDNC) technique to schedule SVC packets. According to packets weighting on the vertices of a well-structured two-layered IDNC graph, an effective heuristic algorithm is proposed to schedule the most valuable SVC packets combinations within acceptable complexity. Extensive simulation results verify the effectiveness and the quality of experience enhancement accomplished by the proposed algorithm.

Scalable NOMA Multicast for SVC Streams in Cellular Networks

In this paper, a non-orthogonal multiple access (NOMA)-enhanced scalable video coding (SVC) multicast scheme for cellular networks is proposed. This scheme combines the successive video-layer decoding in SVC with the successive interference cancellation (SIC) in NOMA, which enables a further reduction of the bottleneck effect imposed by cell-edge user equipments (UEs). Aiming at maximizing the overall video quality experienced by UEs in multiple multicast groups, the resource allocation for multiple groups and the scalable multicast scheduling within each group are formulated as a joint mixed-integer nonlinear programming problem. The formulated optimization problem is decoupled into a multi-group resource allocation (MRA) problem and multiple independent intra-group scalable multicast scheduling (IGSMS) subproblems. To solve IGSMS subproblems, we propose an optimal recursive algorithm, for which the optimal transmit power for each layer of the superposition coding needed in each iteration is derived in a closed form. The MRA problem is optimally solved via a knapsack approach. Extensive numerical results demonstrate the improved performance of the proposed NOMA-enhanced SVC multicast scheme over several baseline schemes.

Demonstration of OpenFlow-Controlled Network Orchestration for Adaptive SVC Video Manycast

Software defined networking (SDN) makes networks programmable and application-aware by decoupling network control and management (NC&M) from data forwarding and leveraging centralized NC&M to facilitate user-customized routing and switching. Inspired by these, this paper investigates how to realize the OpenFlow-controlled (OF-controlled) network orchestration that can facilitate efficient scalable video coding (SVC) streaming to heterogeneous clients. Specifically, we consider real-time SVC streaming and address the situation in which video sources reside in geographically- distributed servers and clients can join and leave the streaming services dynamically. We formulate this as a multi-source multi-destination manycast problem and realize the networking system with an OF-controlled SDN architecture. We first design the OF controller to enable efficient network operations. Then, we focus on solving the multi-source multi-destination SVC video manycast problem and design several algorithms. Initially, an integer linear programming (ILP) model is formulated to obtain the optimal solutions for small-scale problems. Next, we try to make the manycast algorithm suitable for practical implementation, and design two time-efficient heuristics. Simulation results indicate that the heuristics can provide close-to-optimal solutions. Finally, we build an OF network testbed that consists of OF switches, SVC video servers and clients, and perform SVC streaming experiments to demonstrate our design. Experimental results verify that the proposed scheme can allocate bandwidth intelligently and ensure high-quality video streaming. To the best of our knowledge, this is the first work that accomplishes experimental demonstration of OF-controlled network orchestration for adaptive SVC video manycast.

Frame distortion estimation for unequal error protection methods in scalable video coding (SVC)

In many multimedia applications, coded video is transmitted over error prone heterogeneous networks. Because of the predictive mechanism used in video coding, transmission error would propagate temporally and spatially and would result in significant quality losses. In order to address this problem, different error resilience methods have been proposed. One of the techniques, which is commonly used in video streaming, is unequal error protection (UEP) of scalable video coding (SVC). In this technique, different independent layers of an SVC stream are protected differently and based on their importance by using forward error correction (FEC) codes. Accurately analyzing the importance or utility of each video part is a critical component and would lead to a better protection and higher quality of the received video. Calculation of the utility is usually based on multiple decoding of sub-bitstreams and is highly computationally complex. In this work, we propose an accurate low complexity utility estimation technique that can be used in different applications. This technique estimates the utility of each network abstraction layer (NAL) by considering the error propagation to future frames. We utilize this method in an UEP framework with the scalable extension of H.264/AVC codec and it achieves almost the same performance as highly complex estimation techniques (an average loss of 0.05dB). Furthermore, we propose a low delay version of this technique that can be used in delay constrained application. The estimation accuracy and performance of our proposed technique are studied extensively.

A Network-Adapative SVC Streaming Strategy with SVM-Based Bandwidth Prediction

This paper presents an online streaming strategy for SVC (Scalable Video Coding).The crucial technique adopted is the combination of network bandwidth prediction and rating mechanism for different streaming options. An SVM (Support Vector Machine) algorithm is used for prediction of network bandwidth variation, with which the system then evaluates every strategy that can be made at that time. The experiment shows this strategy not only cut down video playing back interruption times, but also improves overall video quality users perceive. Index Terms—Bandwidth prediction, support vector machine, SVC streaming. I. I NTRODUCTION The techniques for video content delivery have evolved from UDP (User Datagram Protocol) to HTTP (Hypertext Transfer Protocol) based methods. HTTP based solutions have many advantages including easy deployment and better utilization of web cache infrastructure. Furthermore, they are Firewall and NAT (Network Address Translate) friendly. Thus many mainstream video providers, such as YouTube, deliver contents via HTTP. The providers also allow users to choose from multiple versions with different quality. To do this, videos will be encoded into different and independent files with much redundant information. So space waste is one shortcoming in mainstream approaches. Another defect is although the mechanism for choosing different video versions is provided; users are not usually making the right choice and suffer from playback interruption or low quality of downloaded videos.

Design QoS-Aware Multi-Path Provisioning Strategies for Efficient Cloud-Assisted SVC Video Streaming to Heterogeneous Clients

We layout a network infrastructure that leverages the storage and computing power of a cloud residing in the core for collecting network status and computing multi-path scalable video coding (SVC) streaming provisioning strategies. Therefore, in addition to its conventional tasks in the application layer, the cloud also gets involved in the network layer for the optimization of routing and forwarding. We call this scheme as cloud-assisted SVC streaming, and use it to further improve the performance of SVC streaming by using close cooperation between cloud and network. Compared to source-routing based provisioning, the cloud-assisted scheme can provide more cost-effective provisioning strategies by utilizing better knowledge of network environment together with more powerful computation power. We then propose several multi-path provisioning algorithms for cloud-assisted SVC streaming in heterogeneous networks. To the best of our knowledge, these are the first proposals to work on the problem of adaptive multi-path SVC streaming under the bandwidth, delay and differential delay constraints. Our design of the provisioning algorithms starts from an approach that is based on Max Flow and an Auxiliary Graph. Several extensions are then made based on this approach to address the situations such as provisioning from multiple sources and provisioning in dynamic network environments with rapid background traffic fluctuations. Simulations in both static and dynamic network environments show that the proposed algorithms can achieve effective performance improvements in terms of request blocking probability, bandwidth utilization, packet delay, packet loss rate, and video playback quality.

Trade-off optimization for scalable video coding streaming in relay-based OFDMA networks

To achieve an optimal trade-off between video quality and energy efficiency in the uplink streaming of multi-user Scalable Video Coding (SVC) videos in relay-based Orthogonal Frequency Division Multiple Access (OFDMA) cellular networks, a cross-layer design framework that jointly selects the Transmission Policy (TP) for SVC video frames, assigns OFDMA subcarriers, and allocates power for each subcarrier is proposed. We apply the dual decomposition method to the problem, and obtain a TP selection subproblem for each SVC video adaptation and a resource allocation subproblem of Joint Subcarrier, Relay and Power Allocation (JSRPA). A second level of dual decomposition is used to divide the JSRPA problem into independent subcarrier subproblems. The proposed Cross-layer Trade-off Optimization (CTO) algorithm is sub-distributed with significantly low complexity. A performance evaluation with typical SVC video traces demonstrates that the proposed algorithm is able to converge and efficiently achieve the optimal trade-off between the video quality and energy consumption at the MSs for uplink SVC streaming.

A resource allocation algorithm for OFDM-based cellular system serving unicast and multicast services

In this article, we propose a resource allocation algorithm for orthogonal frequency division multiplexing-based cellular system that serves users each of which requests a regular service or a multimedia broadcast multicast service (MBMS). We assume that the MBMSs are considered for video services such as mobile TV. In order to efficiently serve the users with heterogeneous channel conditions, we employed channel-adaptive video streams by using scalable video coding (SVC), where a realistic multicast configuration is considered for multicasting the SVC streams. Therefore, we designed the cellular system to serve constant and flexible bit rates for the regular services and the MBMSs, respectively. Thus, we consider three objectives when allocating the bandwidth resources, where total transmit power is regulated. First, the bit rate of each regular service has to be guaranteed. Second, the minimum bit rate of each MBMS for achieving the minimum video quality has to be guaranteed. Third, the average video quality of the users requesting MBMSs has to be maximized. In order to achieve the objectives, we propose to quantify the service quality of each service, and then find the resource allocation that maximizes the total service quality. By using the computer simulation results, we could verify that the three objectives can efficiently be achieved. Also, we could verify that the performance of the proposed algorithm is superior to that of the previous algorithm designed to maximize the total bit rate while guaranteeing the minimum bit rates.

안드로이드 플랫폼에서 온라인 SVC 스트림을 재생하는 비디오 재생기의 설계 및 구현

This paper introduces an implementation of SVC player which runs on Android platform and can play SVC video stream on line from SVC video server. SVC(Scalable Video Coding) is a scalable video encoding technique which supports three scalability such as temporal scalability, spatial scalability, and quality scalability. To implement the SVC player on Android, we implemented a SVC decoder using JSVM open source written in C/C++ as a native part on Android and developed Android UI in Java. Also we built an SVC encoding system off line and an SVC streaming server to conduct on-line SVC streaming experiments. Finally, after we installed the SVC player developed in this paper on Motoroi mobile phone, we evaluated and analyzed on-line streaming performance of the SVC player. The result showed that the player worked well and it had no jitter in streaming with the size of QCIF and 10fps from a fully encoded SVC video source.

Home gateway for three-screen TV using H.264 SVC and raptor FEC

This paper describes the design and implementation of a multimedia home gateway for threescreen television (3STV) service. The proposed in-home wireless network uses scalable video coding (SVC) and unequal error protection with Raptor forward error correction (FEC) for maximizing the quality of experience (QoE) over the variable-bandwidth, error-prone wireless network. The gateway incorporates (a) dynamic SVC layerswitching, which enables the server to perform selecting appropriate layers from SVC bitstreams, (b) adaptive Raptor FEC, which controls the overhead of Raptor FEC according to packet loss rate (PLR), (c) an efficient combination of (a) and (b), and (d) slice group-based selective streaming in the overall gateway architecture. The paper explains the home gateway architecture as well as experiments for performance evaluation as compared to that of traditional SVC streaming. In the experiments conducted, gains in video quality vary from 2 to 5dB in peak signal-to-noise ratio (PSNR), with corresponding subjective improvements. Overall reductions of bit rate at the input to the home gateway vary from 28% to 36%1.

A Sorting Approach of SVC Streaming for Video Transmission

摘要: 该文提出了一种适用于传输的可分级视频编码码流的排序方法。该方法通过对码流的合理选择和对失真的高效近似计算，优先传输率失真性能较好的可分级码流，从而提高了重建图像的质量。该文建立了用于划分复合可分级码流的状态模型，推导出了可分级码流失真的近似计算公式，在一定带宽限制下，采用率失真优化的方法对可分级码流进行排序。仿真结果表明该方法能提高视频流重建图像质量。 关键词: 视频传输 / 可分级视频编码 / 率失真理论 / 码流优先级

A cross-multilayer mechanism design for improving video quality of SVC coded video streams over mobile WiMAX networks

Toward the next generation network (NGN), various mobile devices provide users with abilities of ubiquitous computing and communications, however, with different quality of service (QoS) requirements at the same time. With limited wireless network resource, efficient data transmission is critical to meet different QoS requirements. Scalable video coding (SVC) is expected as an appropriate technology to achieve diverse QoS requirements of multimedia video services in the NGN network. In this paper, we expose a challenge when transmitting SVC video streams over existing open-system-interconnection-based networks. We propose a solution to the challenge and degrade video quality corruption when network resource is stringent. While transmitting SVC streams over QoS enabled mobile worldwide interoperability for microwave access (WiMAX) networks, our proposed cross-multilayer mechanism enables classification and prioritisation of SVC video data according to the significance for decoding dependency. In addition, by completely compatible with mobile WiMAX, our mechanism is easily deployable. Simulations validate performance improvement of our mechanism.

Scheduling and Resource Allocation for SVC Streaming Over OFDM Downlink Systems

We consider the problem of scheduling and resource allocation for multiuser video streaming over downlink orthogonal frequency division multiplexing (OFDM) channels. The video streams are precoded using the scalable video coding (SVC) scheme that offers both quality and temporal scalabilities. The OFDM technology provides the flexibility of resource allocation in terms of time, frequency, and power. We propose a gradient-based scheduling and resource allocation algorithm, which prioritizes the transmissions of different users by considering video contents, deadline requirements, and transmission history. Simulation results show that the proposed algorithm outperforms the content-blind and deadline-blind algorithms with a gain of as much as 6 dB in terms of average PSNR when the network is congested.

Implications of Smoothing on Statistical Multiplexing of H.264/AVC and SVC Video Streams

While the hierarchical B frames based scalable video coding (SVC) extension of the H.264/AVC standard achieves significantly improved compression over the initial H.264/AVC codec, the SVC video traffic is significantly more variable than H.264/AVC traffic. The higher traffic variability of the SVC encoder can lead to smaller numbers of streams supported with bufferless statistical multiplexing than with the H.264/AVC encoder (and even less streams than with the MPEG-4 Part 2 encoder) for prescribed link capacities and loss constraints. In this paper we examine the implications of video traffic smoothing on the numbers of statistically multiplexed H.264 SVC, H.264/AVC, and MPEG-4 Part 2 streams, the bandwidth requirements for streaming, and the introduced delay. We identify the levels of smoothing that ensure that more H.264 SVC streams than H.264/AVC streams can be supported. For a basic low-complexity smoothing technique that is readily applicable to both live and prerecorded streams, we identify the levels of smoothing that give (bufferless) statistical multiplexing performance close to an optimal off-line smoothing technique. We thus characterize the trade-offs between increased smoothing delay and increased statistical multiplexing performance for both H.264/AVC, which employs classical B frames, and H.264 SVC, which employs hierarchical B frames. We similarly identify the buffer sizes for the buffered multiplexing of unsmoothed H.264 SVC, H.264/AVC, and MPEG-4 Part 2 streams that give close to optimal performance.

SVC bitstream adaptation in MPEG-21 multimedia framework

Scalable video coding (SVC) is the most promising video format for applications of collaborative communication. MPEG-21 standard has newly emerged to enable the interoperability of multimedia delivery in heterogeneous environments. In this paper we study adaptation of SVC bitstream in the context of MPEG-21 multimedia framework. For interfacing SVC bitstream with MPEG-21 based adaptation system, we propose three SVC specific adaptation operators. Based on our previous work with multidimensional video adaptation, we present an effective approach, using MPEG-21 DIA AdaptationQoS description tool, to model QoS control for SVC adaptation. Then we show how the operator values could be computed from that representation. For the actual adaptation at bitstream level, we propose a procedure to remove the unnecessary NAL units from an SVC bitstream. The result of this study enables QoS management of SVC streaming in an efficient and standardized manner.