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.

Caching collaboration and cache allocation in peer-to-peer video systems

Providing scalable video services in a peer-to-peer (P2P) environment is challenging. Since videos are typically large and require high communication bandwidth for delivery, many peers may be unwilling to cache them in whole to serve others. In this paper, we address two fundamental research problems in providing scalable P2P video services: (1) how a host can find enough video pieces, which may scatter among the whole system, to assemble a complete video; and (2) given a limited buffer size, what part of a video a host should cache and what existing data should be expunged to make necessary space. We address these problems with two new ideas: Cell caching collaboration and Controlled Inverse Proportional (CIP) cache allocation. The Cell concept allows cost-effective caching collaboration in a fully distributed environment and can dramatically reduce video lookup cost. On the other hand, CIP cache allocation challenges the conventional caching wisdom by caching unpopular videos in higher priority. Our approach allows the system to retain many copies of popular videos to avoid creating hot spots and at the same time, prevent unpopular videos from being quickly evicted from the system. We have implemented a Gnutella-like simulation network and use it as a testbed to evaluate the proposed technique. Our extensive study shows convincingly the performance advantage of the new scheme.

An optimal bandwidth allocation strategy for the delivery of compressed prerecorded video

The transportation of prerecorded, compressed video data without loss of picture quality requires the network and video servers to support large fluctuations in bandwidth requirements. Fully utilizing a client-side buffer for smoothing bandwidth requirements can limit the fluctuations in bandwidth required from the underlying network and the video-on-demand servers. This paper shows that, for a fixed-size buffer constraint, the critical bandwidth allocation technique results in plans for continuous playback of stored video that have (1) the minimum number of bandwidth increases, (2) the smallest peak bandwidth requirements, and (3) the largest minimum bandwidth requirements. In addition, this paper introduces an optimal bandwidth allocation algorithm which, in addition to the three critical bandwidth allocation properties, minimizes the total number of bandwidth changes necessary for continuous playback. A comparison between the optimal bandwidth allocation algorithm and other critical bandwidth-based algorithms using 17 full-length movie videos and 3 seminar videos is also presented.     

Reducing channel zapping time in live TV broadcasting over content centric networks

Channel zapping delay is a big challenge in delivering TV service over the Internet infrastructure. Previous research works have studied this delay, its components, and solutions to decrease it. Unfortunately, the best proposed solutions reduce the delay at the expense of increasing bandwidth usage or decreasing the received video quality. After channel switching, the Set Top Box (STB) or player application should buffer sufficient frames before starting to play the received video. However, the buffering process takes place at the playback rate and leads to a delay which is inversely related to the buffer duration. Regarding Information Centric Networking (ICN) paradigm, this paper introduces a new channel zapping protocol that aims to remove the synchronization and buffering delays while maintaining the bandwidth utilization and also the received video quality. The general idea of the proposed solution is to exploit the in-network caching feature of the ICN to retrieve the frames from the network at the network speed. Although the analyses show that the proposed zapping protocol eliminates the delay dependency to the buffer duration, network throughput becomes the bottleneck instead. So, novel solutions have been proposed to reduce the queuing delay as the main component of network delay. These solutions include two new caching algorithms, a new cache replacement algorithm, and applying scheduling methods to the forwarding queues. Simulation results show that increasing link rates, using the proposed caching and cache replacement algorithms, and applying an appropriate scheduling method will greatly reduce the zapping delay without sacrificing the bandwidth or video quality.     

基于MPEG视频流的动态带宽分配算法

ATM是兴起的宽带网标准,基于报文的视频正是宽带网上的一个典型应用.变位率视频的传输方法为恒定的视频质量提供了可能,但是在传输过程中,报文的丢失、延迟和延迟抖动等因素都会影响视频质量,因此有必要提供QoS保证.提出了两种新的在ATM网上进行MPEG视频传输的动态带宽分配算法,一种是动态计算算法,另一种是动态虚拟缓存算法.在这些算法中,根据允许的丢包率,动态地调整MPEG视频带宽以保证QoS.     

A weighted segment-based caching algorithm for video streaming objects over heterogeneous networking environments

Traditional caching technology is not applicable to cache video streaming objects over heterogeneous networking environments. The popularity of mobile devices in the heterogeneous networking environments make the access of Internet content become a common phenomenon. To support different mobile devices in the heterogeneity networking environments, a transcoding proxy is used to transcode different versions of the streaming videos according to clients’ requests. In this paper, we propose a weighted caching replace strategy for video streaming objects over heterogeneous networking environments. A new caching algorithm with static weight transcoding graph and dynamic caching relation tree is introduced. The proposed algorithm is compared with LRU, LFU, CP and PF cache algorithms in three parts: hit ratio, byte hit ratio, and average transmission delay. Experimental results show that the proposed algorithm outperforms than traditional LRU, LFU, CP and PF cache algorithms.     

Efficient segment-based video transcoding proxy for mobile multimedia services

To support various bandwidth requirements for mobile multimedia services for future heterogeneous mobile environments, such as portable notebooks, personal digital assistants (PDAs), and 3G cellular phones, a transcoding video proxy is usually necessary to provide mobile clients with adapted video streams by not only transcoding videos to meet different needs on demand, but also caching them for later use. Traditional proxy technology is not applicable to a video proxy because it is less cost-effective to cache the complete videos to fit all kinds of clients in the proxy. Since transcoded video objects have inheritance dependency between different bit-rate versions, we can use this property to amortize the retransmission overhead from transcoding other objects cached in the proxy. In this paper, we propose the object relation graph (ORG) to manage the static relationships between video versions and an efficient replacement algorithm to dynamically manage video segments cached in the proxy. Specifically, we formulate a transcoding time constrained profit function to evaluate the profit from caching each version of an object. The profit function considers not only the sum of the costs of caching individual versions of an object, but also the transcoding relationship among these versions. In addition, an effective data structure, cached object relation tree (CORT), is designed to facilitate the management of multiple versions of different objects cached in the transcoding proxy. Experimental results show that the proposed algorithm outperforms companion schemes in terms of the byte-hit ratios and the startup latency.     

Caching video objects: layers vs versions?

Because Internet access rates are highly heterogeneous, many video content providers today make available different versions of the videos, with each version encoded at a different rate. Multiple video versions, however, require more server storage and may also dramatically impact cache performance in a traditional cache or in a CDN server. An alternative to versions is layered encoding, which can also provide multiple quality levels. Layered encoding requires less server storage capacity and may be more suitable for caching; but it typically increases transmission bandwidth due to encoding overhead. In this paper we compare video streaming of multiple versions with that of multiple layers in a caching environment. We examine caching and distribution strategies that use both versions and layers. We consider two cases: the request distribution for the videos is known a priori; and adaptive caching, for which the request distribution is unknown. Our analytical and simulation results indicate that mixed distribution/caching strategies provide the best overall performance.A shorter version of this work has appeared in Proc. of IEEE International Conference on Multimedia and Expo (ICME), Vol. 2, pages 45–48, Lausanne, Switzerland, August 2002     

Reducing bandwidth requirement for delivering video over wide area networks with proxy server

Due to the high bandwidth requirement and rate variability of compressed video, delivering video across wide area networks (WANs) is a challenging issue. Proxy servers have been used to reduce network congestion and improve client access time on the Internet by caching passing data. We investigate ways to store or stage partial video in proxy servers to reduce the network bandwidth requirement over WAN. A client needs to access a portion of the video from a proxy server over a local area network (LAN) and the rest from a central server across a WAN. Therefore, client buffer requirement and video synchronization are to be considered. We study the tradeoffs between client buffer, storage requirement on the proxy server, and bandwidth requirement over WAN. Given a video delivery rate for the WAN, we propose several frame staging selection algorithms to determine the video frames to be stored in the proxy server. A scheme called chunk algorithm, which partitions a video into different segments (chunks of frames) with alternating chunks stored in the proxy server, is shown to offer the best tradeoff. We also investigate an efficient way to utilize client buffer when the combination of video streams from WAN and LAN is considered.     

MSC: a multi-version shared caching for multi-bitrate VoD services

Recently, many Video-on-Demand (VoD) service providers try to attract as many users as possible by offering multi-bitrate video streaming services with differentiated qualities. Many researches focus on video layered coding (e.g., scalable video coding, SVC). However, SVC is not widely used in VoD industry. Another solution, multi-version videos, can be classified into online transcoding and pre-stored multi-version videos. Online transcoding is a CPU-intensive and costly task, so it is not suitable for large-scale VoD applications. In this paper, we study how to improve caching efficiency based on pre-stored multi-version videos. We leverage the sharing probability among different versions of the same video and propose a multi-version shared caching (MSC) method to maximize the benefit of caching proxy. If the desired version is not in the cache while the higher neighbor version is in, MSC transmits the higher version streaming to user temporarily. In this case, MSC can make full use of the caching resources to improve the cache hit ratio and decrease users’ average waiting time. Simulation results show that MSC outperforms the others in the cache hit ratio and the average waiting time.     

A dynamic caching algorithm based on internal popularity distribution of streaming media

Most proxy caches for streaming videos do not cache the entire video but only a portion of it. This is partly due to the large size of video objects. Another reason is that the popularity of different parts of a video can be different, e.g., the prefix is generally more popular. Therefore, the development of efficient cache mechanisms requires an understanding of the internal popularity characteristics of streaming videos. This paper has two major contributions. Firstly, we analyze two 6-month long traces of RTSP video requests recorded at different streaming video servers of an entertainment video-on-demand provider, and show that the traces provide evidence that the internal popularity of the majority of the most popular videos obeys a k-transformed Zipf-like distribution. Secondly, we propose a caching algorithm which exploits this empirical internal popularity distribution. We find that this algorithm has similar performance compared with fine-grained caching but requires significantly less state information.     

Utility-oriented resource allocation for 360-degree video transmission over heterogeneous networks

Immersive media streaming, especially virtual reality (VR)/360-degree video streaming which is very bandwidth demanding, has become more and more popular due to the rapid growth of the multimedia and networking deployments. To better explore the usage of resource and achieve better video quality perceived by users, this paper develops an application-layer scheme to jointly exploit the available bandwidth from the LTE and Wi-Fi networks in 360-degree video streaming. This newly proposed scheme explores the saliency of video contents, prediction of users' view and channel status information to maximize the system's utility in a multi-RAN environment. It also determines the optimal association of users with multiple Wi-Fi access points (APs). Besides, a novel buffer strategy is proposed to mitigate the influence of short-time prediction problem for transmitting 360-degree videos in time-varying networks. The promising performance and low complexity of the proposed scheme and algorithms are validated in simulations with various 360-degree videos.     

Content-based adaptive compression of educational videos using phase correlation techniques

A serious bottleneck towards multimedia e-learning is the non-availability of required bandwidth to view the lecture videos at good resolution because of large size of lecture videos. Content-based compression of video data can greatly enhance the bandwidth utilization over scarce resource networks. In this paper, an educational video compression technique is presented that dynamically allocates the space according to the content importance of each video segment in the educational videos. We present a phase-correlation-based motion estimation and compensation algorithm that assists in the compression of important moving objects in an efficient manner. Temporal coherence is exploited in a two-phase manner. First, the frames with high similarity are categorized and encoded efficiently. Second, the compression ratio is adapted according to the frame content. Shots that are of high importance are stored at a higher bit rate as compared to the frames of relatively low importance. The importance and priority of the frames is computed automatically by our algorithm. Results over several hours of educational videos and comparison with the state-of-the-art compression algorithms illustrate the high compression performance of our technique.     

端到端MPEG-4 FGS视频TCP友好的平滑传输

着重研究了Internet上MPEG-4 FGS(fine grained scalable)视频流的自适应平滑传输,其主要目的在于,在网络带宽变化的情况下,提供稳定的视频回放质量.提出了一种新的基于TFRC(TCP-friendly rate control)的MPEG-4 FGS端到端视频流传输系统框架,在此框架的基础上,首先假设完整的可用带宽变化已知,并且提出了一种离线的自适应平滑算法.此后,给出一种基于改进的ARAR(autoregressive autoregressive)预测技术的在线自适应平滑算法.最后,以NS-2为实验平台进行了模拟实验.模拟实验表明,提出的离线和在线自适应平滑算法可以充分利用可用网络带宽,并且能够在可用网络带宽持续波动的情况下保证接收方的回放尽可能地平稳,从而达到获得最佳视觉效果的目的.     

基于可扩展视频服务器集群的视频点播系统设计

随着计算机技术和高速网络技术的发展,视频点播系统已变成现实,并且具有巨大的潜在需求。利用视频对象简介能够给用户一个友好的互动收视环境。可扩展视频服务器集群可以适应未来的用户需求的快速增长。视频对象分段技术和前缀缓存技术使视频文件按照一定的缓存策略以分段方式分布在协作式的缓存服务器集群中,以利于服务器集群的负载平衡和减少对用户的启动延迟。系统还引入了IP组播技术来减少对网络带宽的开销。该文提出了混合式的协作缓存和IP组播的方式交付视频对象,并描述了它是如何工作的。     

A video caching policy for providing differentiated service grades and maximizing system revenue in hierarchical video servers

A video server normally targets at providing abundant bandwidth access and massive storage in supporting large-scale video archival applications. Its performance is sensitive to the deployment of the stored contents. In this paper, we propose a video caching policy for a video server, based on the knowledge of video profiles, namely: access rate, video size and bandwidth, tolerable rejection probability, and rental price. We consider the video server as having a hierarchical architecture which consists of a set of high-speed disk drives located in the front end for caching a subset of videos, and another set of high-capacity tertiary devices located in the back end for archiving the entire video collection. The front-end disks particularly, are organized together by employing a proposed data striping scheme, termed the adaptive striping (AS), which is flexible on heterogeneous disk integration. The proposed policy determines what video set should be cached, and how to arrange them in the front-end disks with two objectives in mind: (1) offering differentiated service grades conforming to the video profiles as well as (2) maximizing the overall system revenue. We simulate the system with various configurations, and the results affirm our effective approach.     

An efficient server bandwidth costs decreased mechanism towards mobile devices in cloud-assisted P2P-VoD system

Recently, more and more devices with small buffer size such as PDAs or mobile phones are joining in the VoD system, which leads to two major challenges: how to efficiently distribute their bandwidth resources with small buffer size, and how to provide assistant mechanism to make them playback smoothness. In face of this situation and for the purpose of decreasing the server bandwidth costs, we propose a peers’ downloading mechanism called NCDLT to solve above challenges. It contains two algorithms. The first is neighbors and chunks downloading selection (NCS) algorithm and it ensures peers to find neighbors who can provide video data with lower refusal rate. The second is distributed linear taxation algorithm (DLT) and it makes peers with lower capability acquire enough download rate to reduce the request to servers. The simulation results demonstrate that our algorithms can offload the server bandwidth costs and improve the download rate of peers with small buffer size.     

多通道Haar-like特征多示例学习目标跟踪

目的 提出一种基于多通道Haar-like特征的多示例学习目标跟踪算法,克服了多示例跟踪算法在处理彩色视频时利用信息少和弱特征不能更换的缺点。方法 首先,针对原始多示例学习跟踪算法对彩色视频帧采用单通道信息或将其简单转化为灰度图像进行跟踪会丢失部分特征信息的缺点,提出在RGB三通道上生成位置、大小和通道完全随机的Haar-like特征来更好地表示目标。其次,针对多示例学习跟踪算法中Haar-like弱特征不能更换,难以反映目标自身和外界条件变化的特点,提出在弱分类器选择过程中,用随机生成的新Haar-like特征实时替换部分判别力最弱的Haar-like特征,从而在目标模型中引入新的信息,以适应目标外观的动态变化。结果 对8个具有挑战性的彩色视频序列的实验结果表明,与原始多示例学习跟踪算法、加权多示例学习跟踪算法、基于分布场的跟踪算法相比,提出的方法不仅获得了最小的平均中心误差,而且平均跟踪准确率比上述3种算法分别高52.85%,34.75%和5.71%,在4种算法中获得最优性能。结论 通过将Haar-like特征从RGB三通道随机生成,并将判别力最弱的部分Haar-like弱特征实时更换,显著提升了原始多示例学习跟踪算法对彩色视频的跟踪效果,扩展了其应用前景。     

Fine-Grained Scalable Video Caching for Heterogeneous Clients

Much research has focused on caching adaptive videos to improve system performance for heterogeneous clients with diverse access bandwidths. However, existing rate-adaptive caching systems, which are based on layered coding or transcoding, often suffer from a coarse adaptation and/or a high computation overhead. In this paper, we propose an innovative rate-adaptive caching framework that enables low-cost and fine-grained adaptation by using MPEG-4 fine-grained scalable videos. The proposed framework is both network-aware and media-adaptive; i.e., the clients can be of heterogeneous streaming rates, and the backbone bandwidth consumption can be adaptively controlled. We develop efficient cache management schemes to determine the best contents to cache and the optimal streaming rate to each client under the framework. We demonstrate via simulations that, compared to nonadaptive caching, the proposed framework with the optimal cache management not only achieves a significant reduction in the data transmission cost, but also enables a flexible utility assignment for the heterogeneous clients. Our results also show that the framework maintains a low computational overhead, which implies that it is practically deployable.