A fair server adaptation algorithm for HTTP adaptive streaming using video complexity

Multimedia Tools and Applications - The increasing popularity of online video content and adaptive video streaming services, especially those based on HTTP Adaptive Streaming (HAS) highlights the...     

Adaptation logic for HTTP dynamic adaptive streaming using geo-predictive crowdsourcing for mobile users

The increasing demand for video streaming services with a high Quality of Experience (QoE) has prompted considerable research on client-side adaptation logic approaches. However, most algorithms use the client’s previous download experience and do not use a crowd knowledge database generated by users of a professional service. We propose a new crowd algorithm that maximizes the QoE. We evaluate our algorithm against state-of-the-art algorithms on large, real-life, crowdsourcing datasets. There are six datasets, each of which contains samples of a single operator (T-Mobile, AT&T or Verizon) from a single road (I100 or I405). All measurements were from Android cellphones. The datasets were provided by WeFi LTD and are public for academic users. Our new algorithm outperforms all other methods in terms of QoE (eMOS).     

On the trajectory of video quality transition in HTTP adaptive video streaming

HTTP adaptive video streaming matches video quality to the capacity of a changing context. A variety of schemes that rely on buffer state dynamics for video rate selection have been proposed. However, these schemes are predominantly based on heuristics, and appropriate models describing the relationship between video rate and buffer levels have not received sufficient attention. In this paper, we present a QoE-aware video rate evolution model based on buffer state changes. The scheme is evaluated within a real-world Internet environment. The results of an extensive evaluation show an improvement in the stability, average video rate and system utilisation, while at the same time a reduction in the start-up delay and convergence time is achieved by the modified players.     

A client-driven media synchronization mechanism for RTP packet-based video streaming

Media synchronization is used to correctly playback a video stream with its associated audio. To support synchronization between video and audio streams transported over IP networks, an RTP/RTCP protocol suite is usually employed. In conventional server-driven media synchronization, the server needs to periodically transmit an RTCP sender report (SR) packet to provide the client with a UTC time in NTP format corresponding to the RTP timestamp carried by each RTP packet. In this paper, we propose a precise client-driven media synchronization mechanism for an RTP packet-based multimedia streaming service. In the proposed method, the server does not need to send any RTCP SR packets for synchronization. Instead, the client device derives the precise normal play time (NPT) for each video and audio stream from the received RTP packets containing an RTP timestamp. Simulations show that the proposed client-driven synchronization method can provide accurate media synchronization without employing an RTCP SR packet and accordingly reduce the initial synchronization delay, the processing complexity at the client device, the number of required user datagram protocol ports, and the amount of control traffic injected into the network.     

Battery-aware rate adaptation for extending video streaming playback time

Multimedia streaming applications are computation and network intensive that put a high demand on battery usage of mobile devices. Battery usage forms an important metric in user satisfaction, as increased battery consumption results in faster battery depletion and eventually leads to battery outage. In this paper, we propose an adaptation technique, referred as Battery-Aware Rate Adaptation (BARA) scheme, which adapts to the appropriate bit rate to prolong the battery lifetime. BARA considers both the wireless channel conditions, as well as the device’s battery level, to determine the best transmission rate for optimizing the mobile battery consumption. Actual experiment and simulation results corroborate that compared to the conventional techniques, BARA can save more than 40% of battery power, while extending the video playback time by 20%.

     

An adaptation rate upper limit for adaptive control under modelorder mismatch

An upper limit on the adaptation rate of an adaptive control algorithm when there exists model order mismatch is given. Under the condition that an operator H₂ is strictly positive real (SPR), the adaptive control algorithm is stable for a sufficient small estimation rate ∈. An upper limit for ∈ is explicitly given     

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。     

Effective bandwidth based scheduling for streaming media

We propose a class of rate-distortion optimized packet scheduling algorithms for streaming media by generating a number of nested substreams, with more important streams embedding less important ones in a progressive manner. Our goal is to determine the optimum substream to send at any moment in time, using feedback information from the receiver and statistical characteristics of the video. To do so, we model the streaming system as a queueing system, compute the run-time decoding failure probability of a group of picture in each substream based on effective bandwidth approach, and determine the optimum substream to be sent at that moment in time. We evaluate our scheduling scheme with various video traffic models featuring short-range dependency (SRD), long-range dependency (LRD), and/or multifractal properties. From experiments with real video data, we show that our proposed scheduling scheme outperforms the conventional sequential sending scheme.     

基于无线网络环境移动流媒体码率自适应研究

基于校园无线网络环境,研究了流媒体视频码率自适应技术.利用分布式实时转码系统保证直播流视频转码的实时性,并根据校园无线网用户的特殊性,研究了首次接入视频码率选择策略,以减少码率切换次数.实验证明,这种方案在无线网络环境发生变化时,保证了视频播放的流畅性,为用户提供了友好的体验.     

Disseminating streaming data in a dynamic environment: an adaptive and cost-based approach

In a distributed stream processing system, streaming data are continuously disseminated from the sources to the distributed processing servers. To enhance the dissemination efficiency, these servers are typically organized into one or more dissemination trees. In this paper, we focus on the problem of constructing dissemination trees to minimize the average loss of fidelity of the system. We observe that existing heuristic-based approaches can only explore a limited solution space and hence may lead to sub-optimal solutions. On the contrary, we propose an adaptive and cost-based approach. Our cost model takes into account both the processing cost and the communication cost. Furthermore, as a distributed stream processing system is vulnerable to inaccurate statistics, runtime fluctuations of data characteristics, server workloads, and network conditions, we have designed our scheme to be adaptive to these situations: an operational dissemination tree may be incrementally transformed to a more cost-effective one. Our adaptive strategy employs distributed decisions made by the distributed servers independently based on localized statistics collected by each server at runtime. For a relatively static environment, we also propose two static tree construction algorithms relying on apriori system statistics. These static trees can also be used as initial trees in a dynamic environment. We apply our schemes to both single- and multi-object dissemination. Our extensive performance study shows that the adaptive mechanisms are effective in a dynamic context and the proposed static tree construction algorithms perform close to optimal in a static environment.     

An adaptive multimedia streaming dissemination system for vehicular networks

An adaptive seamless streaming dissemination system for vehicular networks is presented in this work. An adaptive streaming system is established at each local server to prefetch and buffer stream data. The adaptive streaming system computes the parts of prefetched stream data for each user and stores them temporarily at the local server, based on current situation of the users and the environments where they are located. Thus, users can download the prefetched stream data from the local servers instead of from the Internet directly, meaning that the video playing problem caused by network congestion can be avoided. Several techniques such as stream data prefetching, stream data forwarding, and adaptive dynamic decoding were utilized for enhancing the adaptability of different users and environments and achieving the best transmission efficiency. Fuzzy logic inference systems are utilized to determine if a roadside base station or a vehicle can be chosen to transfer stream data for users. Considering the uneven deployment of BSs and vehicles, a bandwidth reservation mechanism for premium users was proposed to ensure the QoS of the stream data premium users received. A series of simulations were conducted, with the experimental results verifying the effectiveness and feasibility of the proposed work.     

A speculative load adaptive streaming scheme for efficient video delivery

Video on demand services require video broadcast schemes to provide efficient and reliable performance under various client request loads. In this paper, we have developed an efficient request load adaptive broadcast scheme, speculative load adaptive streaming scheme (SLAS), that requires lower service bandwidth than previous approaches, regardless of request rate. We have provided both analysis and simulation to show the performance gain over previous schemes. In this paper, we provide the theoretic upper bound of the continuous segment allocations on channels. We found that the number of allocated segments of the SLAS is close to the theoretic upper bound when compared with other schemes over various numbers of stream channels. Our analysis of client waiting time is almost identical to simulation results about all client requests. By simulation, we compared the required service bandwidth and storage requirements of the SLAS scheme and other schemes and found the SLAS scheme is an efficient broadcast scheme as compared to well known seamless channel transition schemes.     

Pyramid coding based rate control for constant bit rate video streaming

In this paper, a novel pyramid coding based rate control scheme is proposed for video streaming applications constrained by a constant channel bandwidth. To achieve the target bit rate with the best quality, the initial quantization parameter (QP) is determined by the average spatio-temporal complexity of the sequence, its resolution and the target bit rate. Simple linear estimation models are then used to predict the number of bits that would be necessary to encode a frame for a given complexity and QP. The experimental results demonstrate that the proposed rate control scheme significantly outperforms the existing rate control scheme in the Joint Model (JM) reference software in terms of Peak Signal to Noise Ratio (PSNR) and consistent perceptual visual quality while achieving the target bit rate. Finally, the proposed scheme is validated through experimental evaluation over a miniature test-bed.

     

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.     

An adaptive peer-to-peer live streaming system with incentives for resilience

Recently, there have been a lot of research efforts on peer-to-peer (P2P) live streaming services. P2P systems can be easily deployed since a participating peer’s resources (i.e., upload link bandwidth) can be exploited to distribute contents. However, how to adapt to leaving peers and how to encourage peers to contribute resources voluntarily are still challenging issues. In this paper, we propose Climber, an adaptive P2P live streaming system with incentives for resilience. Climber is based on the hybrid structure of a tree and a mesh, so as to achieve self-improvement and adaptation to users’ dynamic joining and leaving. Moreover, Climber substantiates an incentive mechanism that provides better resilience for peers with more upload bandwidth allocated. Simulation results reveal that Climber significantly reduces the topology maintenance cost compared to SplitStream and NICE-PRM. Also, simulation and analytical results verify that Climber can bound the level of disruption by dynamically adapting to the user churning rate.     

试论一种自适应3G网络流媒体速率控制算法

随着我国3G移动网络的发展,流媒体业务已经成为了我国移动通信系统中的一个重要组成部分.对3G移动无线网络而言,流媒体的服务质量常常受到无线链路的不稳定性影响,同时还受到客户端缓存和处理能力的制约.本文从自适应AIMD速率控制算法设计入手,并通过仿真实验验证自适应AIMD速率控制算法的性能.     

An improved adaptive control for robust adaptation

An adaptive control law consisting of an integral and proportional adaptation is suggested. It is shown that the addition of the proportional adaptation term to the control law improves the performance of the adaptive system. Although this is done in the context of a first-order system, it is believed that this may also be the case for higher-order systems. The scalar case is only discussed. Simulation results are presented to complement the theoretical developments