CAREER: Bandwidth Allocation Techniques for Video-on-Demand Systems

职业：视频点播系统的带宽分配技术

• 批准号: 9875493
• 负责人: Wu-chi Feng
• 金额: $ 32万
• 依托单位: Ohio State University Research Foundation -DO NOT USE
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-15 至 2001-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9875493&HistoricalAwards=false
• 关键词: CAREER; Bandwidth; Allocation; Techniques; Video

As networking and multimedia technologies continue to advance new video-based applications such as digital libraries and video-on-demand services will become increasingly more common, requiring the efficient network transmission of compressed stored video streams. For constant-quality video streams, however, the efficient allocation of network resources is complicated by several factors. First, compressed digital video data has much larger bandwidth requirements than textual data, and hence, place much larger bandwidth requirements on the network. Second, compressed digital video data can exhibit significant burstiness in bandwidth requirements at multiple time scales. In particular, stored video content will typically be much more complex than "live" videoconference type video streams, resulting in much greater long-term burstiness. Finally, due to the continuous nature of digital video, stringent guarantees on network jitter and delay may be required (especially for live-video transmission).To efficiently allocate network resources for the delivery of compressed video streams, bandwidth-smoothing techniques have been introduced to take advantage of a priori information that may be available for a video stream. The bandwidth smoothing techniques that have been presented thus far have not considered the interactions of bandwidth smoothing algorithms with network delivery mechanism. The proposed research will address the integration of bandwidth smoothing techniques into current networking mechanisms in two key areas:1. Bandwidth Smoothing over ATM - ATM networks are a popular networking technology because it provides some minimum rate guarantees as well as different classes of service. In this study, we will investigate the interactions between bandwidth smoothing techniques and three of ATM's classes: constant-bit-rate (CBR), variable-bit-rate (VBR), and the available-bit-rate (ABR) services. In the first part, we will investigate the efficient mapping of bandwidth smoothing algorithms into the CBR and VBR services. In the second part of this subtask, we will investigate the mapping of bandwidth smoothing techniques into the ABR service class. In particular, the ABR service class provides a minimum cell rate guarantee and, in times of relatively low network load, an available cell rate which allows the applications to send more than their minimum cell rate that has been guaranteed. We will investigate techniques for shaping video streams into the ABR minimum cell rate while taking advantage of the available cell rate to enhance the video stream when possible.2. Bandwidth Allocation Techniques for Best-Effort Networks - Many of the current approaches for delivering video across best-effort networks such as the Internet do so by monitoring network feedback and altering the video frame rate or video frame quality to fit within the available resources. For stored video streams, these algorithms typically do not take advantage of the a priori information available from stored video, resulting in video frame rates delivered to the user that are more variable than necessary. In this study, we will investigate techniques for the efficient streaming of stored video across best-effort networks that take advantage of the a priori information to smooth the video frame rate delivered to the user.The solutions in this project will be evaluated using two methods. First, the solutions will be evaluated and refined through simulation studies using captured and compressed video data. In the later stages of this project, we will implement a simple streamed video delivery system that will demonstrate the effectiveness of the proposed solutions. We will evaluate the proposed solutions using (1) the Internet, (2) the Ohio Computing and Communication ATM Research Network (OCARNet) which connects six institutions within the state of Ohio, and (3) vBNS - the very high speed backbone network that we have access to through the Ohio Supercomputing Center.The contribution of this project will be to answer the following question:What is the best way to take advantage of a priori information in the delivery of stored video streams across networks, which may provide varying guarantees of network bandwidth?Through the intelligent management of network resources, a client-side buffer, and the a priori information avail-able from stored video streams, the solutions developed in this project will allow us to deliver the highest video quality to the user. We expect that this work can serve as a catalyst for the development of future stored-video applications such as digital libraries, distance learning, and video-on-demand.

随着网络和多媒体技术的不断发展，新的基于视频的应用，如数字图书馆和视频点播服务将变得越来越普遍，这就要求压缩存储视频流的有效网络传输。然而，对于恒定质量的视频流，网络资源的有效分配由于几个因素而变得复杂。 首先，压缩的数字视频数据比文本数据具有大得多的带宽要求，因此，对网络提出了大得多的带宽要求。 其次，压缩的数字视频数据在多个时间尺度上的带宽需求可能表现出显着的突发性。特别地，存储的视频内容通常将比“实况”视频会议类型的视频流复杂得多，从而导致大得多的长期突发性。最后，由于数字视频的连续性质，可能需要对网络抖动和延迟的严格保证（特别是对于实况视频传输）。为了有效地分配用于压缩视频流的递送的网络资源，已经引入了带宽平滑技术以利用可用于视频流的先验信息。 目前提出的带宽平滑技术没有考虑带宽平滑算法与网络传输机制的相互作用。拟议的研究将解决带宽平滑技术集成到当前的网络机制在两个关键领域：1。 ATM网络是一种流行的网络技术，因为它提供了一些最低速率保证以及不同的服务等级。在这项研究中，我们将调查带宽平滑技术和ATM的三类：恒定比特率（CBR），可变比特率（VBR），和可用比特率（ABR）服务之间的相互作用。在第一部分中，我们将研究有效的映射到CBR和VBR服务的带宽平滑算法。在这个子任务的第二部分中，我们将研究带宽平滑技术到ABR服务类的映射。特别地，ABR业务等级提供最小信元速率保证，并且在网络负载相对较低的时候，提供允许应用发送多于其已保证的最小信元速率的可用信元速率。我们将研究将视频流整形为ABR最小信元速率的技术，同时利用可用的信元速率来增强视频流。 用于尽力服务网络的带宽分配技术-当前用于在诸如因特网的尽力服务网络上传送视频的许多方法通过监视网络反馈并改变视频帧速率或视频帧质量以适应可用资源来实现。对于所存储的视频流，这些算法通常不利用从所存储的视频中可用的先验信息，从而导致传递给用户的视频帧速率比必要的更易变。在这项研究中，我们将调查技术的有效流存储的视频在尽力而为的网络，利用先验信息，以平滑的视频帧速率交付给用户。在这个项目中的解决方案将使用两种方法进行评估。首先，将通过使用捕获和压缩的视频数据进行模拟研究来评估和改进解决方案。在这个项目的后期阶段，我们将实现一个简单的流视频传输系统，以证明所提出的解决方案的有效性。 我们将使用（1）互联网，（2）连接俄亥俄州内六个机构的俄亥俄州计算和通信ATM研究网络（OCARNet），以及（3）vBNS -我们通过俄亥俄州超级计算中心访问的超高速骨干网络来评估所提出的解决方案。该项目的贡献将回答以下问题：在通过网络传输存储的视频流时，利用先验信息的最佳方式是什么？这可能会提供不同的网络带宽保证？通过智能管理网络资源、客户端缓冲区和存储视频流中的先验信息，本项目开发的解决方案将使我们能够为用户提供最高的视频质量。我们希望这项工作可以作为一个催化剂，为未来的存储视频应用程序，如数字图书馆，远程学习，和视频点播的发展。